{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "9a80f8a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from pandas import DataFrame, Series\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3244c8a1",
   "metadata": {},
   "source": [
    "## 灭鼠类别分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "9fed7451",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['类别', '时间', '页码', '排名', '链接', '主图链接', '主图视频链接', '宝贝标题', '宝贝ID',\n",
       "       '销量（人数）', '售价', '预估销售额', '运费', '评价人数', '收藏人数', '下架时间', '类目', '地域', '旺旺',\n",
       "       '店铺类型', '信誉', 'DSR_物流分', 'DSR_物流行业对比', 'DSR_描述分', 'DSR_描述行业对比',\n",
       "       'DSR_服务分', 'DSR_服务行业对比', '适用对象', '品牌', '型号', '净含量', '包装体积', '物理形态',\n",
       "       '毛重', '产地', '省份', '地市', '产品名称', '药品登记号', '材质', 'Unnamed: 40', '电猫',\n",
       "       '电子捕鼠器', '产品材质', '使用对象', '用途', '规格', '智捕型号', '电池容量', '供电电压', '产品尺寸',\n",
       "       '包装尺寸', '功能', '颜色分类', '产品', '牙刷规格', '是否量贩装', '材料', '重量', '洞口', '是否定制',\n",
       "       '长宽高', '三个装', '工艺', '白色双门', '白色单门', '数量', '捕鼠', '灭鼠', '适用范围', '香味',\n",
       "       '包装种类', '体积(ml)', '货号', '重量(g)', '适用空间', '产品PH值', '输出电流', '输出电压',\n",
       "       '输出功率', '机器智能功能', '双猫三用', '大号', '小号', '黑色特大号', '黄色特大号', '洞口尺寸', '样式',\n",
       "       '洞口内径尺寸'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('data/灭鼠杀虫剂细分市场/灭鼠.xlsx')\n",
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "3d73a83b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从上面结果课看出数据特征特别多，所以需要处理一些无关特征\n",
    "drop_columns = ['时间','链接','主图链接','主图视频链接','页码','排名','宝贝标题','运费','下架时间','旺旺']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "b878bae3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(columns=drop_columns, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "276247eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uVf2tqXg1IV+tfa+VqQ4133cFjqBGh7VaTnNy8//yAu4Dhjfxehb4BHgM+DnwG+AVYI/Kf78KXB2Zclv8tjfwEFKe1wBTgZeA26LCvAn8CRiPlPVuwPeAScDtqBH5L5qO+QhwE/AW8DgwCrg57tkWeAEp2buRojsMVeAXgH416Tw+nvGbiMOBSNDb1Vw/B/gBmtO/beV6H9SwPQecAfwVKfm3gLfintsiL+6K+/sCt0QaHgEeBP4DfIAarLeAB5BlfAdqAF+PtHdBCv9l4HngXeDfIVD/Bd5GAv0UsCpS3AdE3r4GXIqU1F3ABcAywJMRz/vj/YgI+zzUoN6HKs/Dkd8PAyOQ1f4qMDnivmmU3y+jzO4Avhll8VyEvWSk+Z54/QjJ1VcinEuAq+J1TU2e3Qo8GulaOv7zbIQ7MvL4sfj+UEUWt4xyfQIp91Min5+OfPwFcGfcvxpa3v07JFfjga2BKyP/rkK9l3siHUdGfr+LZPwrEceVUWN+PHBhPOs+VNYPRnxvQnXid0hu3kdl/zckD1OQnOwXcbsdKf9ngFMqMtyp8rlv5Ndi8d89gd2B7VHP61Fg7XidFXGaGGXwQpTB8CjXEcCn8d4u8mo4cHpNfl1fowhvjs9dK78XzxgRr4cjHx9BMvVk5MXawO/j2r0V5f1Y5OcjSO9YlM0lSP6fiHx8ADgt8urd+HxalPlD1XjVxrWO7w9V0rMMUV8qv40CzgbGzImunWc+dXffNDb6mlb52YDrgf7A79z9xwBm1gMJ0N/MbHPgYFRRHgCGmtnrQHvgQ7Tw6V2ksC5GymcH1JKvBjhqmX8KTECK7P+Q0lwEKbUlgeVRQV8MHIKsgP1RZi+ElMk5SHAnARchobwPWN7MlkDKZ9GIwxaowh6KKmAvM3uncn0HJBzDkbL7j5ntH/FYHimZLZHS3BgJ0elm9jay+m6KZzyGrPn3kZUyGbgC2AxZ6N3j2qaR7lXcfZSZvRXPGI+UzpuRnx8ihbtv/OcN1AgshBq5vSIuXYE7gYGRnvejHP8E9DOz9sAGZvaveM7JkeZHkKJ5J/L4caRENjCzcajBPAtVvGWi/G5Byu4k1KP6JtAh9hzqH+V3Pup97AxMjzh/Eul4EsnHWvG5mmddUIUt8qxvbFC3BlIIXc1sfaCTma2F5OY4pFwHR74cgBTLS/HcFUImfhPxfcvdDzazv0ZebIaU20JIZh5GindX4GvIQOkOXIbkuytSfNuhBn2VKKfLkcL9DvBn1FCvEHG/N54zGvhWhDUjXqeZ2drASHd/3syWBo4ys50QQ8zsk/jcNcpgAnIbbhffH4t4dAk5mBzleWM8v3At7ooaqW+jnuJ/Ipx7Iy5jgD8Cq5jZRki21jKzp+P/68R9AOOiDo1Bjf4dSEn+J8ZqvgrshBTy9pEXV6F6PhrYyMxuRHrnHVS/DTXQL8YzukX4/0WGYFFXj0JycnjkxRHAEWb2DLCimU0DTgQ2NbN7gE1Q47B6zffOZrZCfMbMTgJ6IlloF3qkO9KTjnp5V5vZshG/j919PC0wrwdKfwJ8XPluwBKoG3aqmW1YudY5Ku3iqJvyKSqUu1ClPggJ/16o0BdDlk0vJGgfoEo7Ld7fRBW6cNP0jefcg3oLiwMbIOE7GglDd6QgCguyC6q4SyHLaSywhZn9DlXwSfHcZVBl6IUsoadRof4rrr+JKsQWEYclgPWQxfQhpaXaD1XmD5A13xFZbtejrvQLSMm8R2ldv4gEdiYSiinx/WSkAIebWXdgHFICa0U6Vou4eITVO+L/sbv/ysy2c/fDY8O2Z1Gj+hjq/cxESmk3YBdUMXpG+WyIGt3rkeI5xt1PATCzp0OZjzCzO1CDd0Lk3/hI86TIr4+Ra+F1ZMH0Az4CNkIKtSuSownIAj8g8rFjPOPtCOf9VvKsK3ILfQD8GDWw1yH5uCPyhyi/FeL9zoh3fyQjSyM5mYFkZbKZrYsamTfjmZMjn46JZw1HSubLSE6eQ430lUgpjkaN7PDIp/fc/Uoz2zHi/QFSpktFnO6LeK4b5dUzntkP9ZoOBgpFMQpwd98yymWEu29RfEaN248iHkMiT+5Ava73Uc+hCyr7fyKZeiiesRlqADsipViMpUxB9XAoskZXi7S/j+rLKcjYOTHisTeqG4cjY+hZZKD908y6VtK3BGp0JyPj7AokR6Ce0c/jc/uI90dIQd8cz9sayVgf1PBOQnpgBVT2I1HduTfKCdSbfRMZEB+5++Yhb1sB79R8fxU4F8mzI13zaKRtpUjT8hGvvqjcV4n/APQ0syfd/UiaYZ4pdTPr4O77m5nFT5uhVn8c8Gvkcvmo8pcnkR/2UGBnM7sXWZrvoIp3C2r5RwI9UAEsGq+tkHWyMSqcXZGFcwzqUi2CWt5nkVLYDCmk5ZBFMxNZqKtEeB9RVuYeEYezUYMxHBUKSEnfjyrjdUjw70MC/qvK9RdQxboDWS5FGFciYXwlnvcQsj4HoQKfCXwfVYZqj6eIW3vki16a2X23qwO3uvsBZnYxcGqkeUSkbXSkc21U2V5CQvQRsIiZjQL6mNkPkKL+XsRnLGoUV0QNwBhU4fZHlWTheG+HFO3SwEQzWw5ZP33COv/A3Qea2ZjI90WQwts84vUAqgSboUo2LtK8Q+TldkhR9I1n7hb5sySAmR0beXFEM3m2DOoFdI24dkdluBTwuLuvF8ptd2TBHYFcNqORYhgfZbY8kq+vRH70BH4WefWHiN9kJAOOyvUpYI8I5wPUQPwsnjUg7rPI447Icu0T6QH1eiaiBuQ9pBw7IyPi6UjLD5H78vXIn+WQzG0c5VPkRW3eFIyuxGORSMMakUdEXF6kHKtph5RXB6S0x6Dy+BHqYU6kVJZ3oDr4QeTfHsBN7n6bmY1E7rLdkDw/7doJ9iw0PvOsmb2CenH3RdlsEmkchGRoEKWRtxjwDdSbmxnfp6G6eSmS/TejnC5FPaBpkc4hSN6XivTug3TBpMibwiCo5uF0wELnFd/bx/PvjvxaEhl0k1H5vovkZU/gTGBfd3+tCDQmazxMC8zLeerjwxp7DimatZH74gjUjfzI3Q+qef0NVdit4r5PUGb8C/m+xiNB3QBlxoT4/gAqhEWR4n4FtbTnIwEHpX0GyriuyL+9Tly/EwnGDFRY3VGGgwq4O+oybgEc6+7PIVfJwcCW7v7vCH99VFm3qLk+DRXo+shd8XNkRXyIWv3CCtwYCcGrqBKC3BPvNpG/7SJvxsX976KG4+pIw8ZmdgvqUUBZ6SziNggpi6WQwro98vE5pBwmI2W9KFJKZ8f1HSOMUZF/Z0U5fA9Zk9siF8uJqLyeRo3iBqiBWBcYGUrTUAPUEzUA16CKehJlhdsPWXODkEIbgBqf/VDDfh5qAL4deTAFycRjkbe1TERydROSk49d5wKMdvcNKvd55MEQVOmPRgp5DFKkg5Hlu0nEbzJSKqughuqiyJvJqIyeQgbJVNQjmIQs/T/GtRUiP2rxygtUZl2QghpM2ZvshmT1fiSvryA5HxD58XvgXDNbCCnqKrXfqzyCGo9idtZHkf7tkOLdATUap6DGcjvUO+iDLNnOyDC5HjVUy6PynRxp+FLN80ai8ZPzKr/dgGSpyA9DsnF7xKeYZGDI8l4r0t494vjriHOhM65GstQFKeql4r89Ue+oJzIwFkP1sT2lAVBllybya7KHgzx4uPLdUSO4mLsvR9lzfNDdH4l7fsjsTKbcZ6tJ5qVSfyoq+JUoUquiSvgoUmxXAZjZwmZ2opldaWY3I+V9ExKUJ1GL+wgqrONQ5R2HFOQ6qBK/iwqnO6rgT6DKMwBVGEdK+11UWK8gf9wb8b4pUj6dKKfgfSleLyLrcMO4b+FI38UR19PN7BvIqjgKKZNNUV43dX1DJEx/RwrjKqTQnkFdyfFI6SwTcT+zEtZikY9QunvGRh5MQsJ4LlKqI1HlugB1kfshK+p9NF7xYKTr6Yjvn1HPZipyd01AlWM6Uqg3ooZwWjxre2S1n4Aq68mU8vUx6jaPQ0r6gIjXW/HbWZGumahino4aidUiDyYj3/3AuHYGZU/lsojjoZF3FyKlu3uU3xjgWqTI/oYapSLPiPSPi3IaH+mr0sHMLkIzEGai8t4e+NTdX437H4xnDo9y+AA1XJcgl+ARSAbvQzL4Kqq8Y5DluA5yE7wceX1WPOeZSjyejzQX8RxvZkUZ9UMuhg4R/gCkPNeMz1cg2eodebUcskI/reQfADEWMut7DT2RjBFpKHz0/0EN5uvI6n0FNcjPI+X+UqRpZORLEd+ipzwVycL2yEXbwczaUTZqG5vZnyrx6A+sZmbfRDIzHDWe+6O6/a34/DdUZ8+P/PgPqt9PoZ7jpIjzy6jMJiKd8L67/xTJxo3ANHcfgurAG0gHXB75WBhJhupez4hrEfdFa74PrabF3d8AFg4ZG+Du04GV4vyJ3mh8YxEzu8jMfubuM919QjPlA8xbn3q1tVoStdy7Ab9FhTrZzDoioSmsp7uRRX8aqqC/RAKxBLISC1/5DFRZxyHhGIJa25uQ5bAiUjD/RC4HQ9ZxD2TRLI4q2FTU7eqBGpC3Iz6TkWDsGvf3RQLjwHJm9k8kXBb3ng28ZWY3IQU4KdLwQFw/ElioMmjTHjV076IGrvBJn4/KaA+kqFejtFCPQwJqSFhnom5bR9QILR55vRNSYu9FHhyJLJV/xX83QYPInyLl2wcJ+ox43qPIWhiALMoZEc/hlN3wmZQ+x8XifRLwkpkdDvwFVeZXI1+fQI3xiqiMH4i8nRbx+E6k/0NkNa4bcXoRNdS7okr4F6QQn0HKdRPkZlsK+VNfR5VuXKT1HxH/Is8syncR1FNaDHjRzNYA2ptZp0j334Ax8f0ppLDeNLOiQV+fcqD521Fuy0Y+/QEp9RORFVn40V9GhskEytkkjhqFVSM9GyIFtlC8uqFe1VJI3m+M+4qG9SZUNzpF2om8PhsZLxvE/b2RkbWdmZ2B5P1DAHefYWYHmJmFRblKhLMakqGVo2y6R7kXYzcPRXr6RL4Ojzz4GDXk2yKX5HuoTi6DZOLbkc4No+x6Ibl4J8K5GTWax8fvIHnogHrJg8xsOJKD+6Jcd4p8WDY+D0QNzJdRI3YNaug+RvXhPWRojEZGycVRtp2RLulsZgfHszdEvdcOEa/eURaGZGtqlNlbzXyvpuWEkKmHkEEyJp4xM+I2M/4/CvWszqIO5tnioxgBno4Uy+Eos0ehAYfLUeveBfilu1cth66oUhQDJH9DPqXfIqU2DgnCUijTPkWF8SJqHFalLIA7kYCPRA1LN1S5VkNWahekwI5H1vL5qEt0r7svFb6x3VAhfIqEeXFmd4f0QxVkY1TJCor7+kVav4aUjNdcvwhVyhsjzYujCv02qkhvISEcjbpu20e6r473U1GXtzPy3U1C0y6Xj/y8Cgn+YUjJ/gNVwIvj847ItbAnqnDfizy4FFlAO0ac10FW9WGo+/zViNMZqHJeGHnUKfK5N2qQNkQVajGkjHcBvo56DVciC+ou5Js+GXXZ340yXAgpjV5oTGUyquAvICXxPirbQ1D5940wf+3uH4b1NzziWuTZu0jZfowU+Oqox7Er6rXcgSrT7THg2ge50b6H3GpXxnM7I+XxL6RAVnP3rc2sc5Td9Uj290EukfciH/eNMD6ItIyl9OOORPJ6dZTJdpGXKyEL9CZk6RcDdhfE/ffH91UjXq9E2F1RnfsnUvCHRl6ciw62ucjMDkK9oYPd/SbTzqvTKvnVK+L6AZLNIZQ+fUNGRQ8kd+1QnRpduW/JyPOiMTgSyXE1v252960BosxudfftIk2Y2Z1IAa4XzxuI6twY5M7pEHE+I+KwHzLi1kdysi5qaEZHWRa9tX/FPUOQPN6E5KIDMqo6IL2zaty3BDAwrOvPxLWO7w+HTC0W+TUCNdo3uPuXzexhVO9WcfcfUC9zMv+xLV6RCSALoFh40ImaRTiV+xeJ9xWjMPojhbgREtItIpM3QRW+X2RM3/heKJLlIpweSBGuGmH0j9+XRi3wWvGMXStx+E4zcdsHWLWFtG4a792KdFeuLVO9p/J7d2CFyvd2Eed2EcdeSDC/BpxXuW9/1PUtBsn6U/oSf1W5b0nKweTFUU+oM2qsvkQsMkKN5H7A3rV5gCpSP1SJ/04sXkED2QOBbeP7sCbypDMa8Czm5fdHPkUi3sWc3z6Rb7WLV7pH2W1Wkz8HEAvKgHXjfY9I59qogm9dxK3Isybit1a8b0A5G2cRYIOa+9YI2epZSUvPyvUhXs5d3j7KbXGkwIrFV1tFGXWKvB+GZnMtHNcPQY3e/kiR90fW57JIGS+LXCw/jv+tjCzilSOPukfeLBrP3qISv+IZK1EuMPsNMpjuR43fG0jZTEQK7ymkeJ6knC12HGrg145X78oztoo4tEd1bZ14rRvvWxOyTqUeEQvGIvxe1TKL37tEupdA7qq1UAPVOV7HEYsUUUNdu5CoC7B2zW9FWfeN907V6zX3tovn1y4cXCby35ABYswub7XfN6h8Xhr4UY3OO4NYPDZHOnZObv5fXpHZ7ZAVtzSfXaBxfSXhQykHJ29HCudoZD0egayTA6JAe1BZgVbzzN6o8hXPXQP5OR9BFvojqPv77yj8YciKGRL3/R01EE+jbtujyOq5M9IzEgl6YY1uHXFbGFkMb0f8eiDLphOaYgfqVi4S6evI7Cvijm4mPZOQm+A1ZEE8h6zxM0MoixH11Sr/WYZYOVoIKpXVi6jr/xSqeH9AFskByDrtHunfNPJmLPLPj6jk2VeAf9bEc7FIx4gIa/1K2jrWISt7U1b2YfH+I8oVgkfG+zmoITstXsXg8PORNw8j2SoGpadU0l/0Ug+LvNu2pXjE98HEKlAkO9ehHsM98azRSCY3AEZU/nd/M+nsgmTzAtQDGlGRhS+hhvPWKJuxyGq7LJ71OpLRS6LcbqjUpQHxef3Ks44G/tpMPEbGe0/KRmBRykZkhXj+BUjm/4Hq8OuoN/ZHVI/uo6zTeyK5KoyX9qgOboXkdEU0P3z/ymtdZLmPQOMgIyKMgchg6IAag8sqirCY6fWNmrBuRVb4/tQ03k2U66B47tpRHoOQv3xWg13z/27A8zW/rYB6CsegsYK9gTUq19sj/bNMEw3BKshA/D/UQBWL9u5q4tmzZLC517z0qd+KXAOfoilb5wBbmtn2qCKMjM9TkDL9BLlmuqLM2A4py/OQwrkaKZTngTXMbBLKuE7ufmk880ykkA6J516LuvbjkRXyGrJy+qNC3A0psiOQ1fgMEpq+qKs3ExXc6qh73wt1IW9HFs+H8f3X8fyZqOIbEsgxyGf7ARLO1ygHbN+MOM4EBsa83Hfit/aoK/hyxJFIy6ER329E/s6Ma78GtjGz1eL3w2K84mEzewO5ly43s7+jirMIUhYXIsHaA3XJByEX0BBkvU1DVsSaZnYYUh7/MLOjTQvCii54H+TLHRz5/0nku6FFPJPcfa9wrRXdcJAynBb/+5VpsdreZnZFhP1nM/s+sJ+ZPYtceBcjN9FFyDX1EfJPTkHTVv+AKmd75BsdhXorL5vZBUj5vIWmzd5DOb4AMi4uNLOiPHePfDg8ynoqWu13LICZrY4U21GAR7x/G9eeQw0NkQ8rID/p6VF+30HuyY8ijI2R/A+Jcu+FFOKT8dxPkaGwM5Kr2yPseyPM04E7zKyPu38Uz1iepvkUwN0n1fw+xczWQ3XsBaRgH0D19RYkNy+gcaBiGuBRUa5nojGwjc1sV2TEfYp6GOujOrw6kvv2EdYBSBn+CpXtMag8LkMy8QGSqzMifndHfk1HxsYHlLNiNkcNkFpx+a7bUU4ouNnMBsdvf0By93M0EL0OMpqeR9NuJ6DG9kfufjsq+75FJkV6r4uv3VGv5GPU2ylm83SJ5/QwLUIrplgeGHm6DHL37osGR88CVjCzc4HL3f3JCOe7qOd0LM3xeVvoNa3bKZHRv4rfPqBclntSvPZHo+V/QwL7LCr4yfH9kCi4k5EyXJ/Sr/gtNAAEankfRJbHKUjw30D+8PHx33HIZzoRCctwZHFci/zO1yHf9gvIF3kNstJXRNbD3cT+J6jLu3Fk9kjU/S0GfgrhHxNh34Ms3+FIWS+KKvKvIw+eQz6/15GP9A6kqD5C/ugrIu7LIutiEmqU7kAW7VTKrvOlkd4hEecxSKl/CfUk1o40b48srslIMG9HDekhSEGOjnyaHM/5BCmYlSIdU5BbZRTl0vrbkCJ8B03lLGThZ/E+HDUqxcDrh3Hv+UgBvEQ5rfQlpNyeQ3LzH9SwnoR6Tz+NdN+FGqSLUYP27whvI0pf6b8jv++J8nyb0rf+KVIQ/0ay9z7qUh8a1+5GA7QTIh5nIFdYzyjbS5EVPx7Jz6j4PiLSvDVqLL+KjJfzkBX8NrLAn4l4PBTlcBPl0vsjoxxujfgOBCZGuPfF+7uoYf4KUlQj4nUjMKmZuvkuMpJ+GPlkSGltHWkcjeTx6ciTKfH+UeT5iEjDVZE3v0HybpV8/GeU362oEf1t5NF3kPL8L6r7o0MGJkS+vQkMj3hugMaBrkBjLmPR4GdhzVeX3U/is/I1IvJxBOUakxGVPLyrIpeDovyKXsxg4O1K+O/F+0pIjg4BelWuG5UeGmpMpkR8/4N02X9RPe2CDJNHUB34FNW/d1B9+32EMSTSvGRLuraYcjYvGBaR7IZmhhyHEr4Y6ib+FBXagcjSuxNV2IHxn4WQgivmixdT2gpLb5K7XwxMMLPLka99e2RVbU05m+RGlLkvA2e4plkuE7/3QMrqXMrVrhui7vCMiIcjq/AylMm3m9nxqEDOQpV8LdQTWQu1zr9H1uHYCHs55H4hnvMRstrXjXufd/fVUcW4FgnXn5GSf59yEOc4JOAT4/u6kYfFTImfICtgIuoyfxNVokMjnDHI4uro7re5+36oR7EWUiT7RxyLWQGXAxMizx5Gwv+1ojzc/V5UmSbHbx3c/VokvPuY2QkA7n5iXMe1cvEx12rGuyOuF6CBxMNQw/yniO8wd185nns95SDWx0jpG3I/9EYKcVz8d3Dk67fdfRTlysrjUE9pOmosRqH1EmtGOgqLeBJSqM+jbvJlkb97I+Njmyi/jyKflkeK7HSktFdGlntX5CM/Ospiq0jntEjP8hHfr6Mu+TXEgi0kg+shmewX6TuXcsFLUR86oNklWyNZPQnVsZ+hLQ/2r3kdgJTKT5C87YrK+zdoAPdDyj2BlkYN6TkR91GUe95MijxYCDWCiyPZnBDXr4u4Xx1x/AjV3cmR/zMpJ1KMQY2bIX2AmRUDoDu71rAcXCnzvxETLcxsQ9PK9PaRRz8GXnL3LUPWCpl7L+IwDuhmZpegbS0eRAbZMahBWSxmwrwIfGRme5m2U+gQeuY61AAvCuxvZseaFrsdg7acWNfMVkKN2ZvufiPSMd+LMhmL6uZGaBxrazSlcjtkaD7v7geaViRfDezmrZwsNy/dL69STpNbFCmF6UjgLorMPA9V0P2R1f0WarFGIgXdAw0I9Yzr3ZHS+yfab+QS1HV6BGX0WfH9VmSZdolrS0RYJ5vZZkjJOrJ8r0Mujj5IOeyLBHwAKuxpqFG4GBXI/sAu7t7DzDaIeD2EWu67UQXdBRXY9AhvGpriNhQp6n7A38KV0TPSshBSRvshBeERp61RA7EwqjjXIUVetPBFt9BQBflaPO+Xkf9FJb6Ccpn34mb2KOXiih0ijPWQAjUkgNPRFM6bIi+mIsvjWsr5uqC5upsCY81sB6SsDkF7ZRzi7pczOx4zAzrEszrH50VQI/5nJAPHm/Zh6RDpOQa5dzpGmi6K/B4T6SgU/N+QcmhvZruj3tMnSLGuhqzJGZTKpWDZiMNxSP4eRdboDOA3UUEx7ctxf+TXsUhRfIwUQR+kuJZF1thrEfaYyLP1kGx0QOU8Fsn9rZQzVsaislw04rB63HsnKruBwDKmxX2dI9wZkQfHRfrOQfKxSzzf4vooNL7wopkV8/S/iSzVV+OemUi+3kdK8r7I1y9FmDshWdw74vhXtEPngWb2CKqnX4o0/l/k/T2ogSzKvB3ltL+ulC6O4+N6F7Ro6SkzOxM1nh2jztzm7h7uuvMo54T3jbT0q5QpMYutA/K5z4iy/Tnqad4Z+fcsMoh2id8ujnxYjnIBUv9Iy3jKKaRroYbto0jHcNRAXQp8LxqCAWiQ9AXTVijvRVhHRXm8ZWZLRTjLmtndSIa298rq0uaYl5b6w0gBjCAGA1CG7IT81/3QYparkLJ5ElXkrZAltDLy0/0RWQWXUHa3+yHLqT+q4KsjoVwGFcQWlefeG69CKR+BFOzzqAK/Fc+eHL85arH7Rxp2QsK4GbLiX0UZ/1VkYb7v7pegnsAOSMGvGa8NkYAfFb+/jwr0CbTxz1dRQ/ACEoqXkDtlAFLu01Gj8UCka1KkvwPqvj+BXCMPxn//D7mEOkZ8i0HPD1GXdQpSyO9EGZ2B3Fi3u/txSJm2R5XkZKSIXkVuosfjGROR8pkRYThqaNaLZ69LOe30+8ASZtbZzP4NrG3aGmC9SFNf1GD9LvJmc9T4HkK5X8qgeM5HaNXnZkgOVkQumC7xflLEfRiSq6WQ/J2LFN8nqLFbCPW41ol4LBxTydZBCupdd989KtMk1OC/7+7fpeQ24MvufjhS2oujhuzuSM9rUX7vUO6suDiy1p5GFtjiyFjphnoV60Y+/yfyelJcLxqwIl+Wi/T1jLJ5DinxDyJ9ayC5fxnJ+12V13B3/znMmiZ4Sdy7G6pn96M61AfVqS6RR69Eup8DXnT3Ae6+iLv3j3y+DljHzPohGTJUh6ZEWBdRLvQZigyUe6K81o1wvxVl9yM0o+Ypd/9yhL8/qiMzY6zoUzNbB9WBsRG/TlG2qyBL/KEYy+qJ5KUL6h3dFZ+vibK5DRmJA5ELawIyIIaimVm/cPdTgU9c0y73Q3LVJ/73TPyn6IlMifQNptRRheFClOtu7r4J8HXXavNe8ewNK9d3r0ehA/PUp3428n/fROl7fieufRlV+FORYL0Urz+iyvcuEtAnkKX9QVyfhrothwB3RFh3o1b8gcjoC5D/7l2kTO9HAv56xOUB1J1+G7XOD6FKMSb++zpqXM5DFsh5SACLLTS/hQTjFdQzKKzLS5EADUUC/U7E/4dI2AqfoKGByZcijNFIiG5CyuCZiO82kd5/RNwmISvkociTG5FC/0X89w7KVW4XIyt88Uj/9fH5XKTkXyL2LUcN2aPI3bAOauReodyb5414/juoYp2NlOIraICrSMedUU7TKfc0uSPCvqfiu1w/rq2FGpUXkPV8D7Kk/hX58S9k7V0e+XwzqjB3Uw6uj6L0e1+LLKjJyN1xBeXUyRGUe648gSzqf0U5v1e551HCVx2/PRrvD0e+F68Xo2y2i+v/RYbBtcjH/AIakP0XKvsuSGYKP/qYSMPHEc40VPb/RQpifOTh28i18e/Iu72QfHSLNC8a6flH/OdRpKAfRIr26Wbq5mvIAFjRy5ka96HGZHKU6adIEb8e8ZxMrLZEM49Gobo0DPUy3kGyMwj1EgZF/n438uZOJLdjkSzfSpyjgBTa1Ij/S0jhPhXp2iV+WxnVlVOQTNwZ8dsXuVzfpvTF31n1tVd/i3wZUbl+HfD3+HxYlG/xfUzlvqmVz51R4/smqvcbxO/FLJZVo7yej++j4vtBkcaRlGN7DyGj6454TQEemBNdO8/cL+5+rGkJ8sLu/oCZ7YGsovOQEO2ChL4b6toVs0HeRT2KSyn3Bx+IMnIcmrHxPJoxMgJZJjuiTLsVWafvIQvgYFQBO8Uzf44UW+FTPA0Nuq6HKuGaSDFOQYJ1NaokSwFnxPOKQZhHUfezL+pqD0Ct8srIqtobWW0/RApmiUhjR8qtApZGvYj+cf9fUOVYGFXkKZQN3AzUtf5L5N2HqLHsEflX+AELH+cakZZlIv27Uw5EXoMq3T2ogiyMGtlvIkW+T5TFxagRA3VZv4IGWn+JFMqYiOfykb+fIgXwVJTb9939MSq4+0gzc9SgLoIs/U9RQ3EosrTWiNsvQY3Rs5GGVyL/nkOV+mNk2T2LGoCPkbX0VWKOtJmdGs94B8nDhAjzNVTeHU0bSa1KOWNmPOo59IkZMn2RG+Lv7v4xgGmb3ZNj1tKtwN2uTamOjLichGRiLFKMS6Lu+UuU2zpsjcq/R5TbmZT7x5+HjJ9V4vlTUeN9IuUq6SFIdvpHOe4ReWgR5pI0TQ804LetmQ2KvBqPXHV/QMplAGp4f4wayYVR41rUrxPi+inIkPldlM91qEfytfjPlpH//Si3dS7k8uZwO85AstjR3deL/B0b946NvDkdNf53Rtij0OEbf477T6mkz5v4XLwvBaxqZg/F98FohtbDcc9g1BNfiBgrirERmxWg+yehz25FDd3xZjaxeIa7Px1uyHFmti2a+fQc0j2dkFJ/E+m1i5B+WDt+6wBMj5lUd1ORuWaZV5Z6pVWrLtD4OlKgQyn3Dj8LKdc70aDRcNRiroiUajukKO8nFsZEWN3i2sKV3/YCriqeW3xHFXa3KJhioUN74In4fC7lSPjhqKJtAmxYCXsX1CX9cXzvFe97I8toF8qBu1WIudxxfc94Ve8pTsy5Mu55mHKBzRpIyFdHXbNdUQMwAFWOU5GFsgtSIFciZXUsUqj7xGs/ZB2thJT63yOPB1bTFs/sROmn7h6/7UbM747vOyPlsS5yAewDXFG5vmXEb22kiIbVPOMu1At5FzXMxeyT61Gv6NdIufwduSmmoh38QA1Rbf4sXQm7HWqY/hbf/4gawauQIh2BGruRSJY+rMTjRaRouyGFvzGSy5dCHoZVvh8U4a8Z+XoM8I+adF6HFPgIpJB+hGRqPBqoHhvxvw0p8kPi9+8CW0UYxbz6lYgFPPH9b2jcaeX4/hIydG5Hctwhfr8cKdHlq3GLay9W6sgdSDH/F/UCxqDG/AeRT/2QEXJU/GcQldOpKOfI34aU1wbIDXkZkvPNkQI+i3IbgHWizH8BdKuEVZ1nPwLpgm8i2fhulNmbqHfyVqR9H1QXPow0jEONTlGu01FjU5T1+1HWxcK161GPcxskQ8cX32tk65km8nEfylOdFkebd1Vnv/w7nl0s/Folvi9LuWPmS8iC3xbpxw58VgYPalHHzmul3kRGHIB8SVXl3Jdyy9yqIu1R+dyFypFzLYS/ckvfa65VG5zqCrfBIbx9q0LXxP83Qo3DOi3c0+R1StdAYeV+qeb64GrlqbnWN+J3eDX+SHFXK0k7KseZxW/NxnUOy7EH8u/u2sz1olI+jazkB1HD85nKUfO/6lTIZSkb0U419zWbP3F9q6hYC1E5rQoNckPFQGghjH7oPNVqvu/exH3LthJOu6i03UOO+0Q9WIhyNeGaQN+5KIed0FTULZHiK5TMSsyumHarfH4w3m+ibCj7ol7laKSYl6TiiqojHvtWPveicvQh6mWvEZ+rx7t9o1oHm5Gfg5Fx91tksFwZMjWKclr0SajRL8ZWTmohnuvXfo+8X6ny25rU6BpgzzrKeGDtdyqKP36v/T6bjDURbt9q2TV5z5wKTVu/okAOoFyuX1g+naj4kij3DulJOTe8XU1Ye6HK24FyD4iqZXkMTSxdj2sbthDHc5ClczUaDLkXWbyTiemKcd+dEe+3QwjHIX/qg8gq+CqyXl5A1s9ByDI4G/hT5XmdgEfmIA9XRNbEGGTtfDN+N2Y/c7Q3peW2bLx/u5pHc1mGi1OepfrlJirKWpXP/6S0VLqhvTCq934lwtmAcun52sjCG0jlnM85iF9zYa5FKJGIy0nMvhp3b9SLXILZzxed7ZzPVp7dG7mIBlEu8a997ctnG6k5amyRQVE9E/ZBpEiORY3Zf5n9OLgnap9VyEZNuIMqnz+z6vZ/kJkOlc/WXJ5Snq3bnFL/fbyPbEImF59LeVmBsudcrGjeMcqqU+W1cHNpizQdG+8H13w/cA7jUj2PtzNwWEv/mZdTGpvjHVRItyHrYv/wX63P7NPLzkRK6ybg7JjWdJ6ZfUS5LeyHqNL9If5zE3Cc6WisK1Dhro98s7MwbYX7VTP7MZq+OD3CHIS6duuhmQWOuqTXIwW+JXJPXGtmA+L675C1tUVM57oWKZWBlHOj20daJqJC2xR4PmaCXIsGh5cys9Mq0ZyBBoPvr4n71yIPx0Wct0C+48WR3/FuM3sinu+Rp0sgd8RmqNX/TW2h1EtMD7sx0nE78m+ejNwaBb+OZ4EsvuXQwFJ/VCZFWJdG2kcjt9CDqBJsgBRjT5RvA4EbI78Kmsuf5sLcCXXLu8ZUwNNRF/46MxtC6Ye+D3XV70I9n92BY83s5+7+QIS5XeV521HOn38aydsByM1U9YUuTLnL4VfQKtljkYtpHeTm2YYWMLP7XMdEdkLyfamZ/YVyJlI/VB7LojK6jnK66rQiHHcfHe/Tm3jMO2bW0d0/dfc7zKw32iP80xbidQ7luE8tM5CL53gz2xm5ddYAtovynAqsZ2aLIDnaEq2tqGUQysO+8d6xUl9moF7+xPi+BnCmmW2DFL2j8vk5cq/MRA1gN1TWnYH+ZvYf1Iu6BMnw0mjs4/kI84mIXzXt7dDssa3MbE/KRYWPIyPuSbTCuzeS53cp96YHyd0OlFuK/w44xsz+7JptMw0Nal/YRJ4A83ZKY7O4pvF8El8/Rv7kbxTXY7BpBVQIi6A50z2QP/G3KIHTkCXcDg0Y7Yys1mVRQV6MRqX3bCIKT6KCXRgp7OvQYNDbaMbMw/Hbscg3uC8a6e+JBgmPRJZysdhlppn9A/m8N0IF9zHlzBOPuBYzAa5Ag2czUaOxG+UB2dugBu9eyiOtqlyIhOYpSr9wJ+Rbd9SbeCjeL0SCCGV+exNhtoiZXWJm58fg4PcoD0AYGM9ZxMz+YWanmlmviFfBMLQFwNPIR1itsCchP/NMVLG6ozwejwYyiymooHKvJ3+qYb6MyudPqHE4A5XD6mjq3S9Qg/MiZQ+rmHX1XbTA6k7U6O9hWkA3MvJkuXjehahXcSnqBVyPrMRjkQy8G68DUCUfgiYI9In0DENy9lETaamlUMyHItlaGimcy5AhcgmS/65oILNX5b9NlruZbWdmm5nZVjFX+nB0BGLxfWNU71piEzQmsAMqm9pyuhCVR4+IZ28kow/EveNR2U9EG949ifzPgyj38lkj0jWYchX0Icjt+Bqqe5ehet8RjdPtiYzDYu79HUgGTo/7h6LGf03KnSSXNLPbkeJ9BLjFZ18w1xRFY7YY0kMd4r0vUtK9kNyvgsruk8rrKORl+Asqv99Ho9sBdOZgs7kezDdL3XRO5oGU8zWXNu1Z3A9l6lqUq7YWQxPvp5kW+HyMBMKRApxIeXr424RvEPnZ7kPpfBE40Mx+6ZqDXeVwJCzfQ1asI2tpBVShZyCB/DoxOo4GnS5AgrhJxHl5JDxdkCKbiQZiLH67jPJElR5Ika8ar8UinhuhmSQvuPu9pn1S7os827UmD5dAFsD5qFEZRLmv+3tIcfVAwtofKZvVTftPD6nMFppTBiNX155o4GZxNHtoChro3BhZiPciK7R78UfX7JcdTYeLT3P3qsK/OOK5NiqH3kjZ9aSsKGMija+4++st5U8TYa6OfLCgPD4N9W66Um4XsD4qg7spz5odghqRdma2DJKPs5Hi2jDCe9zMfgK87O4/NbPN3f3pmrjciSquIZeCo0ZhOdTQ7Ex5Vmo9FPd9Bfmw345ZGH9HZbAoksPbmP20pM9gZsu5+ytI4f4RKcjtUWMNaqR2dvfrzezbrcRrYsju5ErZVMvpZVRfzor7i7gVefoakqW/ug4mAdXHwvq/Ghkxw1CdKizpQgeMRb2kEZQnnPVz99eB35sOeDfXAc6/jzgVs4sGonreEzWu56JB7P1R/Voh5vSv2Uzab0V16ybUu98A1et1kS75C3LrEc/5ursXMomZHYga9L1R77DofRT7xhvl3kRNMj/dL52Q0FW7fJsgJbQJytwV0f7qN1buOQdZ7Heh6VVdUaXojGaBLIpGlBdHSmyJuLY0UrrH1kbEdXbqLfH/vSJOd8bzh6EC2RsJzzmo0lyKXC/7Imtwzfj/SWiGxdtICMfBrNPLj4vPv0C9jWLKnSFr4kw0Qr4RWqRzAHLD7B/3fIAEpeAmyi0Mvh+v6fHblAh75/hPJ+QmuNHdtzWzO919mxDQOeUjd3/VzN5Fiu8+pBwXRQ3VQHcfZ2avxzOK6WKY2dcjH9oBF4Qy+T6Au+9iOl39MuSe+SlSLJtHnh4f+T4duMLM/thK/tSG+XtkKX2KZlS9jSzYKyJOVwIzI22fIkUzPvJ3HDIeLkZy9AtkaRc9nlGUm7GdSI0CNZ06/yJauLS3aRXqTGTBLo/cDkvw2TNIW6KzmX0r8mklM1s5nrGSku4bxtS8HVEDac0H9ZlG6SdoiuXLcb1jE41Uc/SNMulTKZtqOf0JyWMxk2UJynNTn0ZGyArAVWZ2prv/1d3HhqtvayQLP4j7elBuN9Az0t4HlfHvKM8GvSLcOzPR7LkpZnYZ5SZ0C6G8fxrNIpuEZKIHUug9kZv0W+7+zebqjevgkbtD7u6K75OQgXO4u19iZvsg4/XEJgxMRw3OlHDfXBJpftbLg8HvaCnz55tSd/d3gFPCzwVqXcdSLjZaEsWvn9msU1hAFvXDSKm/iwqlE+q29ETKrDeyzIag+eNjUcH1dvcbmonSv5GFMA4JxOrIItgSNQofoe74QGT5nYSUdjskpCD3zQkR762Rots0ri2KhLFz/O8PqBtYdLPfQ8L9HdQAvYGs+/ao4Wqqhd4ANWznIzdCd2RRDovXDsgHvDLqCTzBZ+fptlTR6+EF1Ai/jvK+K+WpSx6+0S6V+w9DvbA7XIcyPMTsdKTcIuA01FXtgSrWwqjMp6NK11r+1Ia5NpKRRVAZTkNzuWciK29RtJXAw3H9bNQzeAU1AH9BvaoBqHe3KPBtM3sAmOHuF4SldS9qiKq8ERX9fNMYTmfU0I+N/Fq3yDNasaorTEdGxTLICBmKyvlupPBPRMrjYeRieK2FsGobpanF97je0n9raYfKpD0qI2P2cuqG8nIJNL1zGMrP36GG83GkmDdC60HWQg3Xx2iywy5I4S6EynUnJCcfUg5ifozKzJFcTGB2Wbead5B7ZRtk/IxFDcXHSMbXRmejjguLeTEzuw/Yyd1n+cSj4TnDtCZntGnF67VonUHv+H4zsGMTCr1gAoC7v2xaCXsgs7swW3SbLwgDpcW2mJ3c/cdmtom7fy9+v4NYBWlmu7v7OHcfZVpOfzuaFvYMciEcg7pbhdK8FRXCgWh60zOocJqjD8rMbsTeFchavAdZP0OQUi6EoFDo3VCDUlhMJyAFNwJZ9KCG6Hh3Xza6ZYvGANfwSuv7BzQDZ5Vwi7R394sj3Rc3FWF3n2lmP0cVZhJSqtshJXYy6g2MQoL5DlposW38/WozWxX4Q02jWQ8dTae1dIv82A4pyh6oQXozrJFukX+LVP77EWqMMLP+yLquchVSiI+gXlE/5OL5ISqP36JK/Wt3f7Cl/GkizCXRQPKDqIHojBrXdmhg7e+oTnyFcvXjRaiCfx3JyKHxv8OQkuoR8SnSWLgeqs/vTGnRg1wERZk8jhTf88iQeAw1KNXBs+aYgVwGI1Fv4wbkhhsZ1x5Bbp7bUcN0aFOBmDaLqjZKbyNLv/g+p+Mub4Ts7uXaMoNqOZkWBnVDivx1JL93IXfeh8hKnxAD0UeZtjT+m7vvbGYz0PjHCshan0q5Ed/bSN5fQvX1UiSfuwIXuPuD8fwRkb7quN0eyE31LtInE5GbcSQq56+gwct7UT17zd0fbyLtXVyLzi5098OiHjwOnBPf90R1wOO5HWsGnbug4/QGo97g99CWBL+P+9sjQ7VZFgSlviSKeOEPPatyrZO7nxot461mtiUS2uWRFXEIaoWXQm6TpVAF3QBVkBVR5fkGUgjTovt/VcVXh2n3wJXdfXq4PJZBFs9zqADeiu97uvsE05FwRyJFfhBSoJ8ii3VxVIm3QAMh6yCFu1Qo9MFAd9P5pKtGa78imnK2kJkdEuloX3w2jSP822tWkkVj+Fe0yOEV017jf4i8ae/apKkz5SHWjwHfNLNXkQW2us++h0m9jEVWbAfKwcRdkbJaCFWm/sBF7v5nM7u18t9vIatxCaS0D4u0tEdl+yka3fcIZywS4gGRruWJBWhmtkor+VMb5spIAfdEA9YzkP/4cMoB2CJt3ZGSeDXy7wLgj+5+TcjQd9HUsmPjWYeHO2idkNe14r1r5E+XcLl0RXK1EFIe1cZxJWRxtq+nEFA3/YOQ2UvdfZ2QzR8iGfwhcLVrD/DbUY+uoHPEe+HIo6JRmoLqUsf4PpFy3Gu2/7ZAP9P42FLxXrhfinL6iZmdjPJwc6TMeyEFXYwL7WRmW1Na/a+ZxuFAxtk01APZJO5ph3qA05Bx1QGVYeHOeNA0aL8+ynMq34vZMDciQ+jTCO9FNEX6E9Sj2wT1iHqh80VfcPdizKHgunDdrRp1fH3U6Hxq2kyuXTxrpmn/o3amvdOJfOqNXHwno0VglwEfmFlhFHSk3JmzSebZGaXNRkBWdyfk632/5tqG7v5QfN4LWSXnIKUwHHWJTkZd8/coZ79sgWYX7B7Xf4UGNP+D/MG/r3nOBigDb0ZCdQOyBP5BuRlWZ2Tl/hQp5qdR9/s/MeBShFVMNXoRuXLucvfxZjbI3Z8xsy7AWdFqL4YsqWWQID+PutQd4vc/oQq/KhKOR9GpP9PjWYYWlNwR35dDVvPtkYZNkdK9Jf7/Emo8xkQcj0YD0LXWct2E4hwb4XaKvHnH3Veo3POAu28cn/+PcssCkMX0s0jLFkjR/gwtf98SNaoPI4XUH7mQ1kDWzxV15E9tmN9H1uCFqCyXRI326kjZf4B6bMUg7X2okj+PlN3fkRtvezP7M3Bo0f02TUlcjdln9LhrgP/iCKcL6iUsgcr5hUjPfkh230OK5Ose53S2kPfXu/uu8fn3lPvrTEd15eZwczb13z3d/a+V74ejGVM7Rh6vj5Ts4miwH+Si7Iosx81biNdBEYfCjdSB2cvpGWSIXGSagtkRKb6bkCvlKmQsXVjEMQyvj5G76VXkanoVNTpD4nlnVp6xNHIZOarTo1HeF+6801FZHxv39ESG2qnx37dRnS9cwSNRY/AWmgSwMpr+vJVr9l41/SeiMvwWasAfiPTvFd/PpDwmsHbap6F6tDEy2B5AbuAj3f2/zeX5bHgbLSaYFy/KpdDtUMVpj5TI0mi60IpImReVdwkkMEdHRu0HnNBC+N+hdCMsU2ecdqPlFWvVlXtN3lfcQ3lW5GeeHWk+bg7yqlhktB3y/9+FRvL3RY3Uesg67T+XZdE53g3NAOlFuQhpt5p7O1Y+P4YU7abFq4mwj4r35ZAlVzxjS1SZe1FZkFGJx/EtxLc4Aq8f5eZlh1Aua+8X8vQVYJ9KmLtX0taH8nzRdsiiH8TsK1QHNfHsnWu+70ppUG1OHEVXc89azaWlubpBuIYqv/1oDsM4Fi2y6xyv76OGs3Pl1ezZnU2E16ocU84M6RrycCnlQq0fV+77Bpo+/AQyvp5GfvlLKQ+R7lx5xkVRbgcQg6eVsHZn9gMtar8PjrQWZdSf2c/RXQjVn+ZWvy4fZXx6yM12qMEovu+AxtyWbeLVj1KxF0cnLkMLK+FrX/PdUp8bwgLbjNIKPQYNRoxGFtl5lHNBn3b3qfG/1YEz3X37mvA6Ate6TvB+wN03Ns0qaIda8U7ufl7c2wE41t1Pj+8PoKl5WzZ33Usrdbi7b9lMGFuiXQDXrNx3DMw6Cu+faHfDJVrJm6PjPx9VXl9GvYq1UU+ne3xfHq1cPaXuzGeWdX6Xx6EDZna/a+vQ4vqsgVKkKD/wmLoYllkfyt6Cuw48qH1G14jbGsUz0KDwaqhRWAKt+lu58p8n3H1ITThbIXkofK9f91hsU3PfvchfPxr5ZXuj2TJbIGVSm6cvoIZmGPCWy3I/G7nOPO4fHZ8XiTw4I551p7tvU3n2RuhUnZdq4zUnmBbk/QIdMP13M3vT3fvNYRiD3P2Z5r7X8f9OyHq9tSU5RoPgtXl6LHKHfQuNN5zl7jdHuLsiy/oIpNh3QLOVDkJW9TJIEV8az3g8frsVKfhtkFXcBTWkr6ON3zrG9xfi/nsqydkSjY09jizmh9zdo7f9AOqljZqDvOmNBl9fjTh2Qe6i6hTWLmivpf+rN9xaWhxFndeY2Rmm+ctNXfuOma0Bsybgn+IaYFgK+eSuQoJR+Ea7oIK/3MxuNk2nOgu1mLMR4RTjC8WgxXdQN/0wypN8QIJRXXTQCfkQv2Nm30GVfLfq9cq1fvG+fhNhfBPNPPgOmgpWzPUejfx5Eyg34m+Jr6NNjj5ACrUv6lJ/EHmyBxLkMyL8Frv4TeHuM4gzOM3sS03ccn2EfxaaVbJh5VpftGz6pHidXFwIV1zBTDQ1rvqM6agS9HJ1/1+r/LcXs5dTQQfgp+6+AZrL3MHM3jCz/5rZv83sQ9OZkasg42AUKo/7KbcXbipPr0azNcYBvcxsE2RtnoSsyOuRO+Ejdz+ZciUnkXfFnO1OyBpe0syWMbO+8VqmibTMRqTjKTN73LRAZiaS32IA8N3WwqiEdbKZXQ38xMyuMrP/mKYA3mZmr8VvV5nZX0xn2zbHDKRooRwcbkqOm8rTNShPWDoT2NO0QhNUtxeLzyujxv2wSG+H+P97qHexTDz7MtQAFAt+eiBZ/Bg1HH3i+/vxmorGXLZHPbZJzH4i1KNm9kNUtue2ptCtmYVcaJrsSZQ9248jHya7+/7AvWZ2Y5TBYyGnj8XrcTP7XUvPXRAGSqucD1xmmptarNRbBM1PnuHl4atQKt+V0SAYqLv+HqpcjnzgPZB/+WzgNnd/vpU4FF2Xd939SjP7urv/YdZFtdRec/90NMAEEtBBNdcnI6tkOhKe85AyqN4zKT5vGHH+CzqG617TIo4JZjab764ZJrkG8wahCjYU+fe7xTN3j/gV87Z3qiPMpjDk8zscLcg4H8nTb1C39WCYZcXfVfnf0sgV9GqE4ZQN3F/NbGd3v9W1nWn1GYsjS657PO9sYEUz+wEaK9kBWWRNcZTJl788atS7ITlZGjUSy6AG76vIOFgDufD2pTwqsZqn05FCWIxyncEQNPj8DlJgPYjpqeF7XzsUuRGrIuN7PySvvVEjMBI1+iNRY9wSzyA/+t1ICULpy4b6VqUWbIZcFe3QbLH3kOIr8vS4yrWvNhUAqME3s06m8YX+8T6tCTl+v5KnuxGDyaiM30b5sRZwQDR8d6HG9gDUSFyPxju+geQbyjr4LZSn30UD3Osii/1gpAf2Qy6RPpXvDyB//F1ohe/maErlPRFuR9RwfAeV8XXN5YGVC7kuQhMXioVcX6fcdrgn6ll0LNKJGnfc/Rwz+7K7D66EOQytLp1mZs+ZWfswrj7DAmWpu0722A+dQP4H02rSM5Ey/gmAmZ1jZr9AVu1pwHR3HxwZ8BTKSENK8j+ogo1Egx0fmmYKzMLMeoWFsrSZPY6Oa3sYDWY1RzXfPgDGu/uf4/UHNCA567q7X+Xa53l8XP9pbRjufhXqGVyK5qhfxOynCcHse4c0R3HvcNQYnoN8db+jtF42Qw3hHsi9UDdm1sc0y+NTL8817YbK6RWkIAmrsz+aLz3L6nT3ge6+vJdnRn69Evwo4EdmNjCeMbPyjKlo4Pp+NFh1ORqgfZJy299/NhHl55GieAkpo8J6PAMpxfHIddcRTX8djBrmicjdA7Pn6XFo9tTx7v4mcUanu18QcTsLKZ3tKJfs/w514TdH+f0YUmL7IjfUvqhSP+XuOwLPxfvc8GPU6J1I03uvNIu7v+buY4gl665JClPRwSHFtY+99RN4PkD17r14b0qOq3m6NeqpzqRsJN+Pe94HpoRr6lnkPvWaZ1xD2Ut5h/KYuqPjfXfKU64OinB3R72GQykPs1kJLTI8Efn3l4r/vI+U/TOu051OQwZIc2s8HjdtbfKS6+zlvpHGl4g9gFwLuYpZRCtTnl1cMMtwDPfV5pV83Lo5hQ4LmFIHcPeP3P1Md9/f3Q9x9295LC8ObkfzSSeijP40FPNdyBK7FrW0e6HW/nF3/4drRsQRaDOdarqnoFVbb7j7mu6+XHTVixF/jZiZrWxmy5n870/Hb0ORRXB0EZiZrYZmCRR0jfsAjjat+nu6CCPoFe+jkMUwyd1PQ26YE4HlzWxNWpnKVMOz7n5QPGcVJKzd0FzbZSKvvokGgeaEqcjvWTSIXyFWYaKusyPl+wNkKT2KGhfiP6dEF/IlM3sRWVAFE1GFOhcJf2czOyAa8UWQMngLVejFkeW2NFKeuyJFXcsqaAB9PVRRt2P2BVhTUb7PQFMypyAFsRSyBKuN+7PRA6lawB3dfT+TP/tctDf5QWha2gzU8LwZeTQz5HBm/H4fsYoVNeJtMcB1P7JeOyNZqpfa3mft9zlhJqUc30vLcvxsNO5vRtxPRAbYChHGDe7+F1Av2d3vrn0G0gnvU65CPxA1TH+lPHxmB1TWhpRsMdPJUe9vSPw+kfLwkokRr+tReU4ys3ORLN2L3HVN0dJCroFoGuNANOOuK5qCfTSwRRg0P0AuvQ1Ns/42AfYrFLlru4NmWdDcL63i7rcBmNlUNIjxLLLEnkEFeimqmL9ElnvvyNiCx70yRz386SNMc7yrrBgNxZpm9jrliUnXA/eYBtamohkXT0ScziVGzs3se8ji7oqsp12RBVGMrF8fCvH7lN3Gn1KugANZb44U36q0sOjAdOjuLynnFxcVcVEksCsiwdoyri0er7oHwUCNLnCHaTOrf1DuiFnlDVSpHOVZtRHdGHVrL0PK58bZg/cRYeH3RhbzyaiSLIQGAU9BUz03Q/lys7tfFnnwf2bWyWefYjYTWddLRHqL+csnUC6d/yXlrn23o4HlH6Au9uFoQB4+uxoXoIeZ7Yi60Jeint4yEd7NaDrt/siy24yywZ8YeXQJUj71uNaaoxqfsagx2Ypy7UezmBYefQcpueL7SqjxnHXbHMbnPJqX4y2QEVM0jF6xeKe4doJ8ESn1j7z53SBnPcPdPzKNx/wGydvqyIIfjBqJ9dFe8I+YDqf/Y/Ebcs10j7gWlv53UWN7Kqq/26Ke7WqoEfqhabLArEH6AqtvIddCqN6D1l9U14q0Q1uOdEFyuAFqfJZg9jJpli+cUg/l9SISADezYqbCxcia64kysjva9+RApETGowrVsYlgQXutbE/pI/8asrommNmjrq10O6DKeC+yci8Hdg6fH8gKHIF8199DCuVWVKG3pZza9DW0PPovqPDuievtUFf9t6ZtgDtR7k2xH1IOzfESUrI/jO7aWqbFL6siX13fyLelkaXxMuWK2LubDLFl3N03glkusf2QVTweKYkTIt7n8dmtU4cgC3gNKlvvVgL+fYT7Q3dfLj4Xro6ByM1T+OS3CZ3QDpXXLOVoWpz0Y9RdPgitsOyB3FEvxOd2lMcmPhJ/nYa69h3i2vLhwy/ytHhfFDXsK8d//ogsrlFIYf8falB+FOH2oTzU+DmkeJ9E00o3Dx871G8Z90M90r0o92gZjIycD5v7Uw2jUaOyWeX7hEhbwZxa6o+hNO9hmn20KbPL8VXA7oWcorzvBrxkZq/E80ciy3V/NEZzZR3PWAwZGfshZXwwmrgwGBgWhuDKqBe2JlKsMyhPueqFym1htI5hOjJ6bkF1dhyyvs8Ffug1e+FY/Qu5PkbG5cWmCREXoLqwOPKbf2BmIzy2EQijYbhpbUF1XLFJvlBKPVr0S5AFd7dpoc+qyC+3IxqMuA1Vqg2QT31npOg7FRZdM9yCpvzNpFwc0t/MlkerAZdCQvksErrTUQXeBVnvFyAF/V48sz0ahNwHDdSeH9c3ins+QYr2W3HP9WiRzTg0kLkl8ocXrfP7wImmgcTptZGP3scfYnzgwnjmt1GFvCKeezJanLI02gHvuRbyo1miHKqujheQtbEQUmQdvNyRb4rH8uxgH6SMfoKUzymVMGetpIzvL1f+d178b2dUAf6LLOtC4RizL8XH3Z81s+PRNNeF3P0E00yXF10bLd3h2txsaeR62QUp4edRWYDqyDvIH+9o4KyYyTKzsCRNe4NPQ/K4RaTlJWT1ngocEwOD16GBs69F5d0DVdj1gDWisVgt3r/ilX1FanH3Vavfo+G52bWKdyfgLtO2GxNbCGMmmuHyqpntFvnYHq1iPJ3w84Yl7MgtsBtaLPgZOQwOQ7tofmxmmyJ3aFWOt0Errc+jlNOhqC5sH79PRnWiOZp6xgRUbh+jutkX+dt7xvNvRIZRf2SYrYpk9h2kwLuisaGvoYZmdVSmP0CGxBjXVgW7A7eb2dbVnoRr8eSWVq4uXhPNvulgZm8jpf1hPHNv00y3FSKtN0XcRpim/Xol3FtM50bU1bh+Ueepr4Gsr4FImUxFgngo5UkoK1HO/+yKlPqNnwms9Wf1QIqwuurSUave2d1XNrMN0aDjmpV7Fket8ljUct/PZ7frXCzi9gaybPdw92PiuWuj08dnrbI1s3Xd/V91xvvAisXbBeXV9qgS9UVjCGPqCWtOiGc9g/yd05ECvMXL2TCdkXXWiZj94u73RXd2X4+ZRqHUb/WaNQVxbXHkgjk0fPmtxcmANd3936bxlDtQfixKebB5b9STmlprgVXC+SYq9ws91j5UrnV396lm1g0plYXR2MW6aGDs6pr7r/dyNehfkcIpVoPORL76JleDtpDOVVCDVayoXbaOQc3iv/uhRrNQUuug/JmBGrZ7I26Gyu5sb+0AZFqX46qcxvdV0QKua+uJd0vPQOcP32ZmPZFeOBHphQnIlXkwqtc3okZlO+SW6Yis+B/F+1O1DZi1Mn/fPru6+Ij4Xt1/ZwW0V8zoyv/ax+/no55dMSBadYF1dfdVmn32F0mpR+Vcy+NEetNmORMLP3v8tiY6qqtNE2Zmfdx9XHzeFCnsu2qfY2brE4qhqftMJyS1c+3ANus6OjS5nnnoCxyhKIe5+29DaRfKAMLyq+TdA2gmyIS47u7+sybCbA/s7+5XfN7xn9+YBs+3QId2fxK//cg1WJ7MQ2oNgOr421yENQi5Iz9E20t8D80qerlyz6rNGRFz/dwFVamb2XaujYiqv60L/MS18vNxtPikaMEeRr7hn6DDbOuZ/ldvXE5DBb2jaYBwe9Sa3oFm26zm7qfHfZuh7t4DaNT6fqTkOiB3whposPAUZBm8ENd6Rbz/lwGz+YZp7+itTdNQuyNrpz3lOaTFasr73H3TuQh/b+Bf7v5iqzd/AbE2WA2atB1mthKy4jtXlXAd/7ufskfzJHKj7onG1l5BvcJzUP0YgXrOG/8vjUctC5RP3cz6IgvvU7RgZAxSDFMpz20sfIwPo0GRd9Gg2bT4vmdbKvRgU9fWAX3RgNsaqDDWQ374LUw7re2FfHgHI9/yz9CA2A1oSuEPIpzxEc5DqFt2Z9x3m2mxlQO/dfcWV44tYBRC+aG7HwJgZku4NjN7gNIHf6eZ/RLNLvgAZq1PIP7TNcIqrI12MOu80JtpYsbBFxEze4PypKhxyPdarAb9O3OwGjRpG6JhnYH0yK+R4fVt066mM5EiPr6FsQSQQv8GMuCGUw62z0Q66gGkG4aigfLjm1LoMYbRm6Y3/OrssW1JUyxQSh0NcDoaHZ+KBiPXRgN9m6FKsKlpK9dX0WDoksh32RtZ6vWO+s8J70cmfx2tQOtNeeLK8+4+ycx+iwrqBTRo8xgaGN2Ecqe2o0zbtnZFPYrjkbXfM/6zvLuva2aLooGTL4RSN7O7gcGmk2QGxW/fRsu8t0FLrgsGxvv3KVeUHly5fnP8vgZSdIYGJLeKAapGoS1XgyZtw0Zo8H17ZEwujdyjt6Bpr3u1otALdkX+c0czra5EcrwEkv9HkM76t2sef1McTqwwreGHEZdmWdCU+nMoI55Fgzb3oa78O5SW4EPhfnkEDUJ+EPffjgYkL0Kj6W3JgWh2y52Uy9z7xO/D4p6LKOdVL4wW9/SP9DyMCtbRqPw7yN0yDbXiiyNltheA6yirX7dxGj43QuHeiQath5n2jT/Py+1Zq1bntykHSqGJEX3X9NFZm17FTBCo/+zOLypzvRo0aRM+RjplY5T/m6PZTm8iX3g9g85LIj/6ZDToOhm5aH+IZP0TtMVxH3f/TQvhuH92GmcxsNzU2pBZLHArSgNHLduKzH5uYzHPFzTf+2M0bexmtMPh+QCm6Ydtyc6oIFZHeTYCTUv6AdqkqzcaTX8z4n4lssBHohVvvVHrWuxQ2AU1QAshBWdoZH6oaXuEAe7e7N4SCxqmtQOdUd48jNIy2cy2NbMjrTzcANQg7osqTPFqitoBaKPc0KlRmdvVoEnbMBnNeHke1c9n0bTon6FDOq5u/q+zKNa5FIvvjIprEpXtTGZfdNVcOHPy+ywWNEu9ObzyOtHM3nb3G8M3+wjw58oslMO9hX0R5pJhwBruPgkodtYbjJTYeGSV34B8cdcgxX0aavH/hCz8s5FFvjPy122BLPrL0bS/h1AjdiVwi5lt5e51rSBbAPgB6lYeilwmp8fnXZGbYT2kzEGulMObCsR0Esxypr13BpnOLzU0n3gks2+/0CjM9WrQpM25A+X/Emh+/rtofnsxnbNz83+dxbj4/7poEeQAVJaFW3gGqiP9gX+Y2a5tra8WVEu94HmUSY8h5Tk+Pm9sWqbfHvmu/mHaqvImyq1325KOwCqmvRg2RKvXnkSFfAJqWIagRvIqyjNNn6VU/tsjV8vpyJr9SfyvK+pxbIYU2HBkLRz1OaTjc8Hdv4mU91Novr6jgeD1kQBvULn9TjP7pZkNMrNlTUe8FeGsBTzm2nvnX+6+YXx+zN2/FM9pFIrVoJdRuqcGI8OguaXxyefLN1DeP4OMrI1QAzsZLXZ6oo4wuiAD5MeoPr8e4TrqyYMWSi6HtqFo83q+oFnqg1DiV0MZshmfPbexC1o1egNwmrvvUvw5ujOPIku4LXmc0ncOUlYT0Qj3Ncg1cx8a/LsOtcrdkatoR9TK/zV+2yzSshSyzLZGA8RLoAGZju5+g5mdaGbHt/V8+8+DyPd20Xt6FVnlB6GZSmPQ3h8FrQ2UFvwvG0ot8HgbrAZN2pyP0ULAheL7TWjW2q/jWj3TaV9CW4gYqgc7UR5S3x4Zcaeh6eT3mM56OLcJa72daYuEKobOet2/Jb/6AjVPPaYMTkNdlKvRoGI7Kuc2Aie7ThnHzPZxbVlbDaP2dO7PI56LuftE08EIMzzOUY1rq6O5xoV//y/uvlfl+ipo+9Cda8KsPTNyqS+K+yUWHx3k7pfH9y6100pjoRiU6wocnRg0oua+u2h6tWefz2Gq6gKD/Q+rQZO2IWawTUcbs52BVoP+GhkmjpTyUXOqX2JB3h/d/WtmtjnwoJfbS3ymrsTvuzP7itJZl5Dhd36zz1vAlHpP5HOdYmb7ufsfa66v6e6Pz5/YzY5pJ76F0TTLKV5zeLOZbeSz73kyp+Ev1khWmpmd1MTPA9H2DXvP6/gkSUuYWR+0T81Ksbr0a8Ci7n7pPHj2SpQDrbXMAMa21INf0JT6UDSgeCba1OcjtJx8NeTP6uVxZuX8xszOQe6UhdBI+SLINdQVbaF7qLtvY9rRbQ3KkXCQ9Xk1mtr4L+S+2Qr54q5DA6bfajAfcpOY2b3uvlnrdybJ/CPGfq5193XnwbPGUs7yK1yUBV1o5QzTBc2nvgiaPtQX+Bvyb92AtqPc0sy+aZ/dL3t+siLK8GfQjnJ3okVJ/wVmmtmfgCHuPrhm3vUINEByPprDehXq4k1E8+17o4HWhiEGmGsZSGVnxiSZn5i2ANkHWei10w0NzWaZFzzn7sPM7Hx3P8LMziNW2rv7D0xbFjfLgqbUN0ADEj2YfRqjA8yLrk89hJvIkVV9PyrwXdFWst9Fq8GOQgsOrjYdFDso3ouW9y13v8jMJqNB063R+aQPo9Wyv0Ij7o1Cba/D0cymfedDXJKkKdoDB3psGDgfKSzz4qzjtag5w7SlPy9oSv0ctEz3LjQlaAqa+rNcrLLDm9jRb15iOs7udjSQ9ws0eDsYKeHfoAVG/0ZT1g5BfvfvI6v0e0ip/40yTYaUeTe04GRmhN13niVqHuA64i1JFnTOMbOJaMD0IzRY/1/gJncfP4/j0tIZps2yIPrUl0Mn+KyFuhztUQaDDl94pJm/z1NMp638AB3a8S906s2RKK4nICV+NDqI+C6k/P+ElPjX0VSp5txIxQj3yM8vBUmSVIlZKp2QW/UZZJANRgbagcAD7t7UgH9bx2MkcgOtgKZRVl1Bhdei2Z0jFyilDhCrRE9D7osr0cT936KpjMNa+u+8wszM3d3MbkArJwcCW7l7cYpPR+Q6uQ1Z3MW0zIKFUMv7KtrYp9hCeADyrbcDRs0LAUqSpCTWXNwV+xndiAZHr4zfv+zu/5gHcbgCuaHhszNg2qEZY02t7QAWMPeLmV2MltzPRK6L1VCruQza3vbyYlvX+czDZvYhGsy8iljKbmZboExfCi1WOh+5WlZH26kWjAImu/suZnaTu38ZtHFVsZjKzH4xz1KTJAlm9l+0O+wQM3serSTvZWbfQrpyIeRF+Lx5BRjnOsN0p/g+2xmmLf15gbLUTYdgnI6Wyq+NdjzcJ37rCPRw92fnWwQrmNmRaCXkNq7Dqa8CjnT3d8zsp8i1sjua3bIX8rWDhGNTdEjzY6h7Vxwmux7qnTyKfHgLyiyfJPn/glhIdz8a09sLrWg/x91vmkfPH4Smc38ZuV+uR/piCjrD9CDgL+5+drNhLEhKHWZl6qHAxcif3svdx87fWH0WM9sM9SS2RfPSBwNPu/uoyj3nufuRMQXpeo8zQa2Z8w3NbDEkRNuicwiP//xTkiRJQeifHdz95vjeB51IduE8jEPh3l0JWMSbOMPUWzg0foFT6o2CmZ3k7j+d2+v13pMkSVJlQd+l8YtMa6sk61lFmSstkySZI1Kpf360tAF+PdfrvSdJkmQWqdQ/P1rza9Xj90rfWJIkc0Qq9c+PtNSTJJnnpFL/HzCzlc1suZrfhsbHo1u7Xk8YbR7pJEkampz9MpfElrqD0f4M1wMvoA29Jrr7rq1dryeMeZuiJEkagQVqRekXjA3cfT0z64C2CL4O+Ka7P1/n9XrvSZIkqZtU6nPPdDNbCvm9XwZOBR3JF4ulWrteTxhJkiRzRLpf5pI46KJKcbKRx4EeLV6vJ4zPIdpJkjQ4qdT/B8ysj7uPi8+bIt/4XcX5ga1dr/eeJEmSekmlPpeY2WnAmu6+YxyDtR0a6Ozg7ge3dr2eMOZHupIk+WKTPvW5Z1N339jM+qKd09Zw90/M7J46r9d7T5IkSd2kUp973jezr6JTjM4GZoT7pGOd1+u9J0mSpG7S/TKXmNmSwAXACHRQ9lR01ugp7v50a9frCWMeJidJkgYhV5TOPTsDX0KnGi0ErApsgPZYr+d6vfckSZLUTVrqc4mZPQps5+6TKr/1AG5x9w1bu15PGPMkIUmSNBTpU597OgKrxIG0VTrXeb3ee5IkSeomlfrc8zg6XLqWJ+u8Xu89SZIkdZPulyRJkgYiB0qTJEkaiFTqSZIkDUQq9SRJkgYilXqSJEkDkUo9SZKkgfh/lgoBbbiRvP8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 检查空值情况 可以看出缺失比例还是挺大的\n",
    "df.isnull().mean().plot(kind='bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "ed2ac8d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看灭鼠市场的整体价格分布\n",
    "sns.histplot(df['售价'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "b17c1779",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>类别</th>\n",
       "      <th>宝贝ID</th>\n",
       "      <th>销量（人数）</th>\n",
       "      <th>售价</th>\n",
       "      <th>预估销售额</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>收藏人数</th>\n",
       "      <th>类目</th>\n",
       "      <th>地域</th>\n",
       "      <th>店铺类型</th>\n",
       "      <th>...</th>\n",
       "      <th>输出功率</th>\n",
       "      <th>机器智能功能</th>\n",
       "      <th>双猫三用</th>\n",
       "      <th>大号</th>\n",
       "      <th>小号</th>\n",
       "      <th>黑色特大号</th>\n",
       "      <th>黄色特大号</th>\n",
       "      <th>洞口尺寸</th>\n",
       "      <th>样式</th>\n",
       "      <th>洞口内径尺寸</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>566054780243</td>\n",
       "      <td>9976</td>\n",
       "      <td>26.8</td>\n",
       "      <td>267356.8</td>\n",
       "      <td>11901.0</td>\n",
       "      <td>11596</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>广东 韶关</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>566054780243</td>\n",
       "      <td>9976</td>\n",
       "      <td>26.8</td>\n",
       "      <td>267356.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11596</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>广东 深圳</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>572115448996</td>\n",
       "      <td>9945</td>\n",
       "      <td>9.9</td>\n",
       "      <td>98455.5</td>\n",
       "      <td>26442.0</td>\n",
       "      <td>3569</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>39868408322</td>\n",
       "      <td>99</td>\n",
       "      <td>29.9</td>\n",
       "      <td>2960.1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>352</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>河南 南阳</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>520282897220</td>\n",
       "      <td>99</td>\n",
       "      <td>39.9</td>\n",
       "      <td>3950.1</td>\n",
       "      <td>559.0</td>\n",
       "      <td>1250</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 79 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   类别          宝贝ID  销量（人数）    售价     预估销售额     评价人数   收藏人数      类目     地域  \\\n",
       "0  灭鼠  566054780243    9976  26.8  267356.8  11901.0  11596  灭鼠/杀虫剂  广东 韶关   \n",
       "1  灭鼠  566054780243    9976  26.8  267356.8      NaN  11596  灭鼠/杀虫剂  广东 深圳   \n",
       "2  灭鼠  572115448996    9945   9.9   98455.5  26442.0   3569  灭鼠/杀虫剂    NaN   \n",
       "3  灭鼠   39868408322      99  29.9    2960.1     20.0    352  灭鼠/杀虫剂  河南 南阳   \n",
       "4  灭鼠  520282897220      99  39.9    3950.1    559.0   1250  灭鼠/杀虫剂    NaN   \n",
       "\n",
       "  店铺类型  ...  输出功率  机器智能功能  双猫三用  大号  小号  黑色特大号  黄色特大号 洞口尺寸  样式 洞口内径尺寸  \n",
       "0   天猫  ...   NaN     NaN   NaN NaN NaN    NaN    NaN  NaN NaN    NaN  \n",
       "1   天猫  ...   NaN     NaN   NaN NaN NaN    NaN    NaN  NaN NaN    NaN  \n",
       "2   淘宝  ...   NaN     NaN   NaN NaN NaN    NaN    NaN  NaN NaN    NaN  \n",
       "3   天猫  ...   NaN     NaN   NaN NaN NaN    NaN    NaN  NaN NaN    NaN  \n",
       "4   淘宝  ...   NaN     NaN   NaN NaN NaN    NaN    NaN  NaN NaN    NaN  \n",
       "\n",
       "[5 rows x 79 columns]"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac9aa618",
   "metadata": {},
   "source": [
    "### 统计不同价格区间的预估销售额"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "e84498c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "bins_prices = [0, 50, 100, 150, 200, 250, 300, 10000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "67da4881",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['价格区间'] = pd.cut(df['售价'], bins=bins_prices, \n",
    "       labels=['0-50', '50-100', '100-150', '150-200', '200-250', '250-300', '300+'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "0fd78edd",
   "metadata": {},
   "outputs": [],
   "source": [
    "sales = df.groupby('价格区间')['预估销售额'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "5bf13a24",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "价格区间\n",
       "0-50       15162086.51\n",
       "50-100      3335060.19\n",
       "100-150     2758086.29\n",
       "150-200      629813.00\n",
       "200-250     2743758.00\n",
       "250-300      237740.00\n",
       "300+         819468.00\n",
       "Name: 预估销售额, dtype: float64"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "ca9e561e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "价格区间\n",
       "0-50       0.590286\n",
       "50-100     0.129840\n",
       "100-150    0.107377\n",
       "150-200    0.024520\n",
       "200-250    0.106819\n",
       "250-300    0.009256\n",
       "300+       0.031903\n",
       "Name: 预估销售额, dtype: float64"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 销售额占比\n",
    "sales_prop = sales / sales.sum()\n",
    "sales_prop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "891de008",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "价格区间\n",
       "0-50       847\n",
       "50-100     165\n",
       "100-150     45\n",
       "150-200     28\n",
       "200-250      7\n",
       "250-300      9\n",
       "300+        16\n",
       "dtype: int64"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 计算各个价格区间的宝贝数量（种类）宝贝ID\n",
    "# 分组有三种方式：groupby pivot_table cross_table \n",
    "# stack 将列索引变成行索引，ustack将行索引变成列索引\n",
    "\n",
    "# 步骤一：根据价格区间和宝贝ID分组计数，可以达到ID去重的目的\n",
    "# df.groupby(['价格区间', '宝贝ID'])['预估销售额']\n",
    "# 步骤二：利用unstack将列索引变成行索引，变成一个宽表\n",
    "# df.groupby(['价格区间', '宝贝ID'])['预估销售额'].count().unstack()\n",
    "# 步骤三：转置让价格变成列索引，取布尔值,存在就是1\n",
    "# df.groupby(['价格区间', '宝贝ID'])['预估销售额'].count().unstack().T != 0\n",
    "# 步骤四：最后一步统计计数\n",
    "product_num = (df.groupby(['价格区间', '宝贝ID'])['预估销售额'].count().unstack().T != 0).sum()\n",
    "product_num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "6f37d469",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "价格区间\n",
       "0-50       0.758281\n",
       "50-100     0.147717\n",
       "100-150    0.040286\n",
       "150-200    0.025067\n",
       "200-250    0.006267\n",
       "250-300    0.008057\n",
       "300+       0.014324\n",
       "dtype: float64"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 计算宝贝数量占比\n",
    "product_prop = product_num / product_num.sum()\n",
    "product_prop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "45d66274",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "价格区间\n",
       "0-50        17900.928583\n",
       "50-100      20212.486000\n",
       "100-150     61290.806444\n",
       "150-200     22493.321429\n",
       "200-250    391965.428571\n",
       "250-300     26415.555556\n",
       "300+        51216.750000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 单宝贝销售额\n",
    "sales_per_product = sales / product_num\n",
    "sales_per_product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "f24ed05f",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "价格区间\n",
       "0-50       1.000000\n",
       "50-100     0.993820\n",
       "100-150    0.884004\n",
       "150-200    0.987723\n",
       "200-250    0.000000\n",
       "250-300    0.977238\n",
       "300+       0.910936\n",
       "dtype: float64"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 竞争度\n",
    "competitive = 1 - \\\n",
    "(sales_per_product - sales_per_product.min()) / \\\n",
    "(sales_per_product.max() - sales_per_product.min())\n",
    "competitive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "1dc44ec3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "product_num.name = '宝贝数量'\n",
    "sales_prop.name = '销售额占比'\n",
    "product_prop.name = '宝贝数比'\n",
    "sales_per_product.name = '单宝贝平均销售额'\n",
    "competitive.name = '相对竞争度'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "85e509ff",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "concat_list = [sales, sales_prop, product_num, product_num, sales_per_product, competitive]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "66a2a697",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "concat_list = list(map(DataFrame, concat_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "98605e76",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "kill_mouse = pd.concat(concat_list, axis=1)\n",
    "kill_mouse.sort_values('相对竞争度', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "a3199448",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>预估销售额</th>\n",
       "      <th>销售额占比</th>\n",
       "      <th>宝贝数量</th>\n",
       "      <th>宝贝数量</th>\n",
       "      <th>单宝贝平均销售额</th>\n",
       "      <th>相对竞争度</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>价格区间</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>200-250</th>\n",
       "      <td>2743758.00</td>\n",
       "      <td>0.106819</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>391965.428571</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100-150</th>\n",
       "      <td>2758086.29</td>\n",
       "      <td>0.107377</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>61290.806444</td>\n",
       "      <td>0.884004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>300+</th>\n",
       "      <td>819468.00</td>\n",
       "      <td>0.031903</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>51216.750000</td>\n",
       "      <td>0.910936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250-300</th>\n",
       "      <td>237740.00</td>\n",
       "      <td>0.009256</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>26415.555556</td>\n",
       "      <td>0.977238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150-200</th>\n",
       "      <td>629813.00</td>\n",
       "      <td>0.024520</td>\n",
       "      <td>28</td>\n",
       "      <td>28</td>\n",
       "      <td>22493.321429</td>\n",
       "      <td>0.987723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50-100</th>\n",
       "      <td>3335060.19</td>\n",
       "      <td>0.129840</td>\n",
       "      <td>165</td>\n",
       "      <td>165</td>\n",
       "      <td>20212.486000</td>\n",
       "      <td>0.993820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0-50</th>\n",
       "      <td>15162086.51</td>\n",
       "      <td>0.590286</td>\n",
       "      <td>847</td>\n",
       "      <td>847</td>\n",
       "      <td>17900.928583</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               预估销售额     销售额占比  宝贝数量  宝贝数量       单宝贝平均销售额     相对竞争度\n",
       "价格区间                                                               \n",
       "200-250   2743758.00  0.106819     7     7  391965.428571  0.000000\n",
       "100-150   2758086.29  0.107377    45    45   61290.806444  0.884004\n",
       "300+       819468.00  0.031903    16    16   51216.750000  0.910936\n",
       "250-300    237740.00  0.009256     9     9   26415.555556  0.977238\n",
       "150-200    629813.00  0.024520    28    28   22493.321429  0.987723\n",
       "50-100    3335060.19  0.129840   165   165   20212.486000  0.993820\n",
       "0-50     15162086.51  0.590286   847   847   17900.928583  1.000000"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kill_mouse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "dcfd608e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.plot(np.arange(kill_mouse.shape[0]), kill_mouse.相对竞争度.values,\n",
    "        color='darkgreen', marker='*', markersize=20,\n",
    "        label='销售额占比')\n",
    "plt.bar(np.arange(kill_mouse.shape[0]), \n",
    "        kill_mouse.销售额占比.values,color=sns.color_palette('husl'),\n",
    "        label='相对竞争度'\n",
    "       )\n",
    "plt.legend(fontsize=18)\n",
    "plt.title('灭鼠市场的价格区间分析', fontsize=20)\n",
    "plt.xticks(np.arange((kill_mouse.shape[0])), kill_mouse.index, color='black')\n",
    "plt.grid(axis='y', ls='--', alpha=0.5)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49ae16ef",
   "metadata": {},
   "source": [
    "> 结果依单宝贝销售额降序,即依竞争度升序,这里销售额占比可以理解为市场份额\n",
    "可见0-50容量大,竞争大,大容量市场(对比的是50-100,容量小,竞争稍小)\n",
    "200-250,竞争小,做高价市场的优先选择,属于机会点\n",
    "可见我们喜欢的类目是:市场份额高(表示更适合大众),相对竞争度低(没人抢).也就是找到闷声发大财的那些个\n",
    "分类去分蛋糕"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d8ddf0b",
   "metadata": {},
   "source": [
    "### 继续分析0-50价格区间的细分市场，探索是否还有可以作为增长点的区间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "9ed4d5c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>类别</th>\n",
       "      <th>宝贝ID</th>\n",
       "      <th>销量（人数）</th>\n",
       "      <th>售价</th>\n",
       "      <th>预估销售额</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>收藏人数</th>\n",
       "      <th>类目</th>\n",
       "      <th>地域</th>\n",
       "      <th>店铺类型</th>\n",
       "      <th>...</th>\n",
       "      <th>机器智能功能</th>\n",
       "      <th>双猫三用</th>\n",
       "      <th>大号</th>\n",
       "      <th>小号</th>\n",
       "      <th>黑色特大号</th>\n",
       "      <th>黄色特大号</th>\n",
       "      <th>洞口尺寸</th>\n",
       "      <th>样式</th>\n",
       "      <th>洞口内径尺寸</th>\n",
       "      <th>价格区间</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>566054780243</td>\n",
       "      <td>9976</td>\n",
       "      <td>26.8</td>\n",
       "      <td>267356.8</td>\n",
       "      <td>11901.0</td>\n",
       "      <td>11596</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>广东 韶关</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>566054780243</td>\n",
       "      <td>9976</td>\n",
       "      <td>26.8</td>\n",
       "      <td>267356.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11596</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>广东 深圳</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>572115448996</td>\n",
       "      <td>9945</td>\n",
       "      <td>9.9</td>\n",
       "      <td>98455.5</td>\n",
       "      <td>26442.0</td>\n",
       "      <td>3569</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>39868408322</td>\n",
       "      <td>99</td>\n",
       "      <td>29.9</td>\n",
       "      <td>2960.1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>352</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>河南 南阳</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>520282897220</td>\n",
       "      <td>99</td>\n",
       "      <td>39.9</td>\n",
       "      <td>3950.1</td>\n",
       "      <td>559.0</td>\n",
       "      <td>1250</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   类别          宝贝ID  销量（人数）    售价     预估销售额     评价人数   收藏人数      类目     地域  \\\n",
       "0  灭鼠  566054780243    9976  26.8  267356.8  11901.0  11596  灭鼠/杀虫剂  广东 韶关   \n",
       "1  灭鼠  566054780243    9976  26.8  267356.8      NaN  11596  灭鼠/杀虫剂  广东 深圳   \n",
       "2  灭鼠  572115448996    9945   9.9   98455.5  26442.0   3569  灭鼠/杀虫剂    NaN   \n",
       "3  灭鼠   39868408322      99  29.9    2960.1     20.0    352  灭鼠/杀虫剂  河南 南阳   \n",
       "4  灭鼠  520282897220      99  39.9    3950.1    559.0   1250  灭鼠/杀虫剂    NaN   \n",
       "\n",
       "  店铺类型  ...  机器智能功能  双猫三用  大号  小号  黑色特大号  黄色特大号  洞口尺寸  样式 洞口内径尺寸  价格区间  \n",
       "0   天猫  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN  0-50  \n",
       "1   天猫  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN  0-50  \n",
       "2   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN  0-50  \n",
       "3   天猫  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN  0-50  \n",
       "4   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN  0-50  \n",
       "\n",
       "[5 rows x 80 columns]"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "d674fa92",
   "metadata": {},
   "outputs": [],
   "source": [
    "df50 = df.loc[df['价格区间'] == '0-50']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "9e32e90c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['0-50']\n",
       "Categories (1, object): ['0-50']"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df50['价格区间'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "c44a4172",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1138, 80)"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df50.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "9b1e095f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>类别</th>\n",
       "      <th>宝贝ID</th>\n",
       "      <th>销量（人数）</th>\n",
       "      <th>售价</th>\n",
       "      <th>预估销售额</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>收藏人数</th>\n",
       "      <th>类目</th>\n",
       "      <th>地域</th>\n",
       "      <th>店铺类型</th>\n",
       "      <th>...</th>\n",
       "      <th>机器智能功能</th>\n",
       "      <th>双猫三用</th>\n",
       "      <th>大号</th>\n",
       "      <th>小号</th>\n",
       "      <th>黑色特大号</th>\n",
       "      <th>黄色特大号</th>\n",
       "      <th>洞口尺寸</th>\n",
       "      <th>样式</th>\n",
       "      <th>洞口内径尺寸</th>\n",
       "      <th>价格区间</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>566054780243</td>\n",
       "      <td>9976</td>\n",
       "      <td>26.80</td>\n",
       "      <td>267356.8</td>\n",
       "      <td>11901.0</td>\n",
       "      <td>11596</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>广东 韶关</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>566054780243</td>\n",
       "      <td>9976</td>\n",
       "      <td>26.80</td>\n",
       "      <td>267356.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11596</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>广东 深圳</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>572115448996</td>\n",
       "      <td>9945</td>\n",
       "      <td>9.90</td>\n",
       "      <td>98455.5</td>\n",
       "      <td>26442.0</td>\n",
       "      <td>3569</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>39868408322</td>\n",
       "      <td>99</td>\n",
       "      <td>29.90</td>\n",
       "      <td>2960.1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>352</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>河南 南阳</td>\n",
       "      <td>天猫</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>520282897220</td>\n",
       "      <td>99</td>\n",
       "      <td>39.90</td>\n",
       "      <td>3950.1</td>\n",
       "      <td>559.0</td>\n",
       "      <td>1250</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>1511</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>573793765449</td>\n",
       "      <td>0</td>\n",
       "      <td>17.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>北京</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1514</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>36825350895</td>\n",
       "      <td>0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>63</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1518</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>573118678210</td>\n",
       "      <td>0</td>\n",
       "      <td>22.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1519</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>550586926422</td>\n",
       "      <td>0</td>\n",
       "      <td>38.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1521</th>\n",
       "      <td>灭鼠</td>\n",
       "      <td>550586926422</td>\n",
       "      <td>0</td>\n",
       "      <td>38.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>灭鼠/杀虫剂</td>\n",
       "      <td>NaN</td>\n",
       "      <td>淘宝</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0-50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1138 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      类别          宝贝ID  销量（人数）     售价     预估销售额     评价人数   收藏人数      类目  \\\n",
       "0     灭鼠  566054780243    9976  26.80  267356.8  11901.0  11596  灭鼠/杀虫剂   \n",
       "1     灭鼠  566054780243    9976  26.80  267356.8      NaN  11596  灭鼠/杀虫剂   \n",
       "2     灭鼠  572115448996    9945   9.90   98455.5  26442.0   3569  灭鼠/杀虫剂   \n",
       "3     灭鼠   39868408322      99  29.90    2960.1     20.0    352  灭鼠/杀虫剂   \n",
       "4     灭鼠  520282897220      99  39.90    3950.1    559.0   1250  灭鼠/杀虫剂   \n",
       "...   ..           ...     ...    ...       ...      ...    ...     ...   \n",
       "1511  灭鼠  573793765449       0  17.16       NaN      6.0      0  灭鼠/杀虫剂   \n",
       "1514  灭鼠   36825350895       0   0.60       NaN     10.0     63  灭鼠/杀虫剂   \n",
       "1518  灭鼠  573118678210       0  22.00       NaN      3.0      0  灭鼠/杀虫剂   \n",
       "1519  灭鼠  550586926422       0  38.00       NaN      0.0      1  灭鼠/杀虫剂   \n",
       "1521  灭鼠  550586926422       0  38.00       NaN      0.0      1  灭鼠/杀虫剂   \n",
       "\n",
       "         地域 店铺类型  ...  机器智能功能  双猫三用  大号  小号  黑色特大号  黄色特大号  洞口尺寸  样式 洞口内径尺寸  \\\n",
       "0     广东 韶关   天猫  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "1     广东 深圳   天猫  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "2       NaN   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "3     河南 南阳   天猫  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "4       NaN   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "...     ...  ...  ...     ...   ...  ..  ..    ...    ...   ...  ..    ...   \n",
       "1511     北京   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "1514    NaN   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "1518    NaN   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "1519    NaN   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "1521    NaN   淘宝  ...     NaN   NaN NaN NaN    NaN    NaN   NaN NaN    NaN   \n",
       "\n",
       "      价格区间  \n",
       "0     0-50  \n",
       "1     0-50  \n",
       "2     0-50  \n",
       "3     0-50  \n",
       "4     0-50  \n",
       "...    ...  \n",
       "1511  0-50  \n",
       "1514  0-50  \n",
       "1518  0-50  \n",
       "1519  0-50  \n",
       "1521  0-50  \n",
       "\n",
       "[1138 rows x 80 columns]"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df.groupby('价格区间').groups['0-50']] # 这种方法和上面的方法等级"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "33045a6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df50 = df50.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "6b044137",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 对df50的价格区间进行调整， 调整为0-10， 10-20， 20-30， 30-40， 40-50\n",
    "df50['价格区间'] = pd.cut(df50['售价'].values, bins=[0, 10, 20, 30, 40, 51], \n",
    "       labels=['0-10', '10-20', '20-30', '30-40', '40-50'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "1fd7e2fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 计算相对竞争度\n",
    "def calculate_compatitive(df, group_by):\n",
    "    # 统计不同价格区间的 预估销售额 (总和)\n",
    "    # 根据价格区间分组\n",
    "    sales = df.groupby(group_by)['预估销售额'].sum()\n",
    "    # 销售额占比\n",
    "    sales_prop = sales / sales.sum()\n",
    "    # 宝贝数量\n",
    "    product_num = (df.groupby([group_by,'宝贝ID'])['预估销售额'].count().unstack().T != 0).sum()\n",
    "    # 计算宝贝数量占比\n",
    "    product_prop = product_num / product_num.sum()\n",
    "    # 单宝贝销售额\n",
    "    sales_per_product = sales / product_num\n",
    "    # 相对竞争度\n",
    "    compatitive =  1 - (sales_per_product - sales_per_product.min())/(sales_per_product.max()-sales_per_product.min())\n",
    "    \n",
    "    product_num.name = '宝贝数量'\n",
    "    sales_prop.name = '销售额占比'\n",
    "    product_prop.name = '宝贝数比'\n",
    "    sales_per_product.name = '单宝贝平均销售额'\n",
    "    compatitive.name = '相对竞争度'\n",
    "\n",
    "    kill_mouse = pd.concat((DataFrame(sales), \n",
    "               DataFrame(sales_prop), \n",
    "               DataFrame(product_num), \n",
    "               DataFrame(product_prop), \n",
    "              DataFrame(sales_per_product),\n",
    "              DataFrame(compatitive)), axis=1)\n",
    "    kill_mouse.sort_values('相对竞争度', inplace=True)\n",
    "    \n",
    "    return kill_mouse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "fbca1e32",
   "metadata": {},
   "outputs": [],
   "source": [
    "kill_mouse50 = calculate_compatitive(df50, '价格区间')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "3e5218d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 可视化\n",
    "def show_competitive(kill_mouse, title, rotation):\n",
    "    plt.figure(figsize=(12,6))\n",
    "    plt.plot(np.arange(kill_mouse.shape[0]), kill_mouse.相对竞争度.values,\n",
    "            color='darkgreen', marker='*', markersize=20,\n",
    "            label='销售额占比')\n",
    "    plt.bar(np.arange(kill_mouse.shape[0]), \n",
    "            kill_mouse.销售额占比.values,\n",
    "#             color=sns.color_palette('husl'),\n",
    "            color='blue',\n",
    "            label='相对竞争度'\n",
    "           )\n",
    "    plt.legend(fontsize=18)\n",
    "    plt.title(title, fontsize=20)\n",
    "    plt.xticks(np.arange((kill_mouse.shape[0])),\n",
    "               kill_mouse.index, rotation=rotation,color='black', fontsize=16)\n",
    "    plt.grid(axis='y', ls='--', alpha=0.5)\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "d023b5e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_competitive(kill_mouse50, '0-50区间的价格分析', 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b058e03",
   "metadata": {},
   "source": [
    "### 店铺类型竞争度分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "8bb7119d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "店铺类型\n",
       "天猫    23551572.38\n",
       "淘宝     2134439.61\n",
       "Name: 预估销售额, dtype: float64"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('店铺类型')['预估销售额'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "a216fe8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "store_categoray = df.groupby('店铺类型')['预估销售额'].sum()\n",
    "store_categoray_prop = store_categoray / store_categoray.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "c782d3fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "店铺类型\n",
       "天猫    0.307181\n",
       "淘宝    0.692819\n",
       "dtype: float64"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = df.groupby(['店铺类型', '宝贝ID'])['预估销售额'].count().unstack().fillna(0)\n",
    "product_num = temp.sum(axis=1)\n",
    "product_prop = product_num / product_num.sum()\n",
    "product_prop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "610597e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "店铺类型\n",
       "天猫    50977.429394\n",
       "淘宝     2048.406536\n",
       "dtype: float64"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sales_per_product = store_categoray / product_num\n",
    "sales_per_product"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "59c185eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "店铺类型\n",
       "天猫    0.0\n",
       "淘宝    1.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "compatitive = 1 - (sales_per_product - sales_per_product.min())/(sales_per_product.max()-sales_per_product.min())\n",
    "compatitive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "76c31b79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>预估销售额</th>\n",
       "      <th>销售额占比</th>\n",
       "      <th>宝贝数量</th>\n",
       "      <th>宝贝数比</th>\n",
       "      <th>单宝贝平均销售额</th>\n",
       "      <th>相对竞争度</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>店铺类型</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>天猫</th>\n",
       "      <td>23551572.38</td>\n",
       "      <td>0.916903</td>\n",
       "      <td>1126</td>\n",
       "      <td>0.500222</td>\n",
       "      <td>20916.138881</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>淘宝</th>\n",
       "      <td>2134439.61</td>\n",
       "      <td>0.083097</td>\n",
       "      <td>1125</td>\n",
       "      <td>0.499778</td>\n",
       "      <td>1897.279653</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            预估销售额     销售额占比  宝贝数量      宝贝数比      单宝贝平均销售额  相对竞争度\n",
       "店铺类型                                                            \n",
       "天猫    23551572.38  0.916903  1126  0.500222  20916.138881    0.0\n",
       "淘宝     2134439.61  0.083097  1125  0.499778   1897.279653    1.0"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cate_df = calculate_compatitive(df, '店铺类型')\n",
    "cate_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "c697366a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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XG2NWG2PGGmNKne+2qhhnJbXXcKZOK7lUc2mv/UVgjTEmopxzRhhjRgB3uzcdzQwet+KM1peWSIYABTe53QAcBLYYY1oc6aTu/ngE56bFdZSyhLMxpinOh6uSN8uVxRcoOhz8DE6ZyVsl2hX891lukbiI1F0aCRaRylKQXH3h/lmQrB31jXFFnIOzSMaIgjl9S5y7GGPMP3BmBsgpsb0nTjLUDaeG9gDwBPDfkjWr7oU6zgb+gXMD3HTAZYx50lr7gPt8l+HciFXWEtHtgJBSaoILFCxwMcW9LLAPcALO3LkX4CwbneB+3QlFjssDehljhgFbcT48dMEZRV1fom1JqThLREfiTH02r5y2hYwxDXHmHJ4P7HJfOxLo5I73DJwa6ndwVogbg1Nb7GeMiceZk3kXTj3vBGutyzjLZF8G/AfnvfoRGGKtTS9y3YtxPgA0xklsX65IvDj/bfi5z3EnTr3wzzilNEX5l/gpIvWMkmARqSx34CR2n7l/L0hUK3JjXFkjmHcDb1trFxdpbyg+crwdZwQyESdJbIW7rraIn3CS1c9xplL7prRpuwq4pxN70xjzLnAhzpLKRb9yvw44k7KT4AIlb0orULDC2zScJP8R/l4eeT3OinfvlBLjpzgj1V8V2ZaPk+RdXk4cWGuz3LNTuIDvyiotKOW4NGPMQOepzTfO8sVXuK+5FGf55UVFYp3hTpz74CTJXXHeq7VF5lr2whndLbriXsmR6S+AF9zX+dD9vCL8+DuxnY3zAeGxUhY6KWhzpFk4RKSOMlVUQiYi9Zx7tK8xkF7agglVdM0AIK+UKbZqNHfSOASnlCTe0/GUxxjjVUpCeSzn8QFOLKMG+HjO2xxoVPDByxhjqqpWWkRqNyXBIiIiIlLv6MY4EREREal3PFITHB4ebmNiYjxxaRERERGpR9asWZNorW1acrtHkuCYmBji4uI8cWkRERERqUeMMaUulKNyCBERERGpd5QEi4iIiEi9oyRYREREROodJcEiIiIiUu8oCRYREZHjlp6VzpjXxpCelX7kxiI1gJJgEREROW4LNy/k07hPWbR5kadDEakQJcEiIiJy3Gb+NNP5+fNMD0ciUjEemSdYRERE6g5rLV+v/xqAWetmYa0lJyeHQ4cOkZaWRn5+vocjlLrE29ubhg0b0rhxY/z9/Y/5PEqCRURE5Lhs3LuRrNwsADJzM/l116/4Z/sTFhZGTEwMvr6+GGM8HKXUBdZacnNzSU1NZefOnbRq1eqYE2GVQ4iIiMhxmf3LbPJceQC4XC627tpKWFgY4eHh+Pn5KQGWSmOMwc/Pj/DwcMLCwjh06NAxn0tJsIiIiByXT+I+ITsvG4CsvCz8XH6EhIR4OCqp60JCQkhLSzvm4ytUDmGMaQZ8Zq3tXcZ+X2Am0Bh401r71jFHJCIiIjXKqKmj+Pznz8vc7+fjV+x3b+PN+j3roYwB4NCgUNpGtK3MEKUe8vX1Pa568yOOBBtjwoAZQINymv0TiLPWng0MNcY0POaIREREpEZ5atRTdGnZhQZ+pacCOXk5h28sJQH2Ml4E+QURHRZdyRFKfXS8ZTYVKYfIBy4BUstp0xf4xP18FdD9uKISERGRGqNds3bEPRDHI8MfIdA3EC9z9NWUXsaLqNAoOjbvSIBvwHHFo4U5pDIcsRzCWpsKR8y2GwB73M9TgWYlGxhjxgHjAKKjo9m+fTsAYWFh+Pn5sX//fgACAwOJiIhgx44dBcfRunVr9u3bR3a2U28UFRVFeno6qalOXt64cWN8fHxISEgAICgoiPDwcHbu3Ak4U2m0bNmSvXv3kpPjfFpt0aIFqamphbUkTZo0wcvLiwMHDgAQHBxMaGgou3fvdt4oHx+io6PZvXs3eXlO8X90dDTJycmkpzv/CJs2bYrL5eLgwYMANGzYkJCQEPbscd4aPz8/oqKi2LVrV+HwfatWrUhMTCQjIwOAiIgI8vLyCgu9Q0JCCA4OZu/evQD4+/vTvHlzduzYgbUWgNatW5OQkEBmZiYAzZo1Iycnh6SkJABCQ0MJCAggPj4egICAACIjIwv7ACAmJob4+Hiyspy7eyMjI8nKyiI5OVn9pH5SP6mf1E/qJyIiIrih5w10a9qNWz+/le2HtpORm8GReBkv/H38aRnakuDAYPLz8wuv4e3tjZeXF7m5uU5bLy98fX0L38+C/s/NzcXlcgHOV+Dzfp3Hp3Gfckm3SxjRdcRh5/Dx8Sl8PwvOkZOTU/jfj6+vLy6XqzAOHx8nHSp4/0qeo+BmrPLOsWPHDho1akRoaGip59i2bRsLFizgmmuuwdfXt/B9z8vLK3xtPj4+pKSkkJ+fT0hISOH788svvxAUFETr1q0Pi6O0cwC8/PLLxMXF8dZbbxV7fwpeS9H3uOQ5Sr62gjj27dvHnj17iI6OJioq6oj95HK52Lp1KyEhITRr1uywfvrpp58IDQ0lJibmmPvJWlv477qsf09lstZW6AEsKWffl0Ck+/ldwOXlnev000+3IiIiUjvl5efZx79+3AbcFGC5nsMec5bPsT9u+9HGbY+ze5P2WpfLVanXHzttrOV67DVvXVOp5z0ew4YNsxERETY5Oblw29KlS21SUpK11tqvvvrKAjY7O9taa+3KlSvt7t27DzvPU089ZcPCwuzKlSuttda6XC57+umn28GDBx9VPA899JAF7LZt2wq3PfbYYzY4ONg2bdrUNmvWrPARHh5u27Vrd8RzvvrqqxawL7zwQoXjaNiwob377rtL3degQQN75513Vvhcpdm4ceMR2+CU7B6Wj1bWPMFrgF7AZ8BpwHeVdF4RERGpYby9vGkb0Zbc/Nxy23kZLwL9Ait1ijRbysIcnp6CbdWqVcyaNYs333yTBg0akJaWhjGGMWPGEBsbyzvvvFM4l62fnx+5ublcccUVtG3blvnz5xeeJzs7m1deeYU2bdrQoUOHwm8lHnnkEZYtW0ZiYmLhaGh+fj7Z2dk0btyYgACnvKRbt278/PPPxWJr06ZN4fO4uDjOOecc/P39ee2111i+fDkffPBB4ejskfj5OTdAFlyvIvz9/QkMDCx1n6+v71Gdq7IddRJsjOkHdLLWvlRk8wxgtjGmN9AJ+L6S4hMREZEa5tBfh7j1g1vJd5V/Z36+K5+kjCRCg0Ir7dolF+bYtG8TnaI6Vdr5j1ZmZibjxo0D4Prrr+f6668HIDc3l5dffpmLL76Y0aNHF0sEJ0+ezL59+1i4cGGxcz311FPs2LGDtLQ02rdvX7g9JSUFb29vpk2bVrgtJyeHrKws5syZQ//+/QEn4ZwwYQJjx45l3759dOvWDYCdO3dy2mmn0b59exo2dOYueO655xgwYABnnXVWhV9rwYeNhIQENm/efNh+614psHXr1oVlId7e3nh7e5d6Pl9f38LEusCGDRuYOnUqL7/8cpV/uKlwEmyt7ev+uQhYVGLfDmPMAJzR4IestVofUUREpA7ak7SHAc8NIDE9sdj2gtrfgvmCC6RkpFTqaG3JhTlm/zLbY0mwtZbrr7+evXv3smHDBpo2bUp+fj6ZmZn4+PgwatQoHnjgATp27FisHj0wMJAnnniCE044oXDbjz/+yOOPPw7A+vXradSoUeG+fv360b59e1599VWAwmuEhIQQFBRU2O7kk0+mQ4cOvPLKK7z00kvExcXRrVs3AgICWLx4MSkpKXz77bcA/PDDDwwbNozPPvsMgAEDBhS7ZnkefPBBHnzwwTL3z5kzh0GDBh3xPF5exW+wfOutt7jtttvIzc1l9OjRnHfeeRWK51hV2mIZ1tq91tpPrLUplXVOERERqTl+i/+Ns586mx2HdhDg8/fX2EF+QZwWfRpf3volp0WfVizhdVlX4chtZSi5MMcncZ8c4Yiqs2/fPjZs2MArr7xCx44dadq0KWFhYURFRQEQHx9Pjx492Lx5M99/73xJ/vXXXxMTE0P79u0Lb5BMTk7m8ssvLyyZiI6OpmHDhoWPH3/8kffff7/w99DQUJo3b87nnxefu/nNN9+kR48evPrqq1x++eWFI8EBAQH07duX3377jdGjRzN69Gh27drF1KlTC3/ft29fhV/3G2+8Ueo9XwXJecHIdEkul4usrCxSUoqniqtXr6Z3795cd9119O/fnw0bNlR5AgxgrPsOvOrUvXt3GxcXV+3XFRERkWOzZscaBk0ehDGGy868jNeWvkZufi7+Pv48fuHj3HH+HXh5eZHvyidubRy+TXxxWRfGGFqEtiCyUWSFrlORhTmKzktc8veSRnYdyf9u/l/FX+hRysvLIyYmpnCmDYDrrruON998k6+++ooRI0ZwzjnnHHbcypUrefvtt7nmmmsYMmQIP//8M3fddRf33nsviYmJxUZle/XqxUknnVRYDpGXl0daWhpBQUE0aPD33M1ZWVmcddZZrF+/vnCU1VqLn58fmzdvZs+ePZxzzjk8+OCDhWUIGRkZPPnkk2zfvp3WrVuX+1qnT5/OtddeyxtvvFFY9nEkkZGRhTOsFJWWlkbbtm3Jy8vj4MGD9OnTh8cff5xevXpV6LwFNm3aRMeOHcttY4xZY609bPreyroxTkREROqoRZsWMeLlEYQHhzPvznlc/sbl5Obnclr0aXx848e0a9ausK23lzchgSG0iWrDnwf+JCMng6SMpAonwU+Neoo/E/9k6/6t/JXz12H7Sya8ZSXADfwa0L5Ze54a9dRRvNKj5+Pjw8KFC5k6dSqrVq1ixowZhYlpwcjuihUrDjuuYKoygHvvvZeIiAjWrFkDQKdOnYqNph86dIh169YVljK4XC6ys7N55plnuPHGGwGnRnj06NH8+eefPP/88/Tq1Ys2bdrQs2dPxo0bVzidH8B9993HsmXLcLlcnHXWWTz55JNl1u1WhtGjRzNmzJjCuLOzswtviGvTpg1ffvllqR8UqpqSYBERESnT5z99zmVvXEb7Zu359o5viQqNIjIkkkkXTyoc/S1NgG8AHZt3ZH/qftKynDmP7/joDtbuWnvEa4YEhNAspBnbD27HZV1HHbOX8aJZSDMaBjTkhnduKLdtl5ZdmHzp5KO+RlEnnXQSYWFh+Pv706nT3/XJZb03Jff37dsXcOqCAbZs2VJ4YxnAWWedRYcOHZg+fXrhtry8PHJzc8nKyiIgIABrLaeddhr3338/S5cupW/fvvj7+xMTE8Ndd9112LVfeeUV8vLyyrwxLiEhoXDu7gIFSXR8fHypN8ZFR0cTHBx82PZOnTpx8cUXl3qdIUOGeCQBBiXBIiIiUoY3lr3B+PfGc9YJZzHrn7No3KAxALNum1Wh440xRDaKrPAocNHjWjZuSZPgJmzct5HMnMwKJcMFyzJ3bN6RIL+gI7avDHv27OHQoUMkJiaSmZnJhg0byMnJ4YQTTigcza3oNGAFi0CEhYUdtu/7779nxowZh20fO3Ys06dPx9/fn8cffxxrLevXr8daS5cuXVi5ciVnnHEGTz31VLEENScnp9yFJCZPnsyTTz5Z6r6yboxbunQp55577hFfZ02hJFhERESKsdby1Jyn+PfMfzP4lMF8Nv4zgvyPP6k8lhHXfFc+T815ise/ebzcG+wCfAN4YMgDTBw88YgjsJXptddeY/LkyYUjs2effTZZWVnMnDmzsBxi7ty5hx1X2o1fBfP1bt++vdyZGqy1JCcnc+jQocLZITIzM3nnnXeYMmUK1lrmzJlD79692bdvHxMnTuTOO+/k+eefLzxHcnIyXbt2LXbOogpi37ZtW+GKbmUpqBUOCQkpt11NoyRYRERECrlcLu759B6eX/A8V/S4greveRtfH1+PxePt5c0pLU7Bz9uv3CTYz9uPzi06V2sCDPDoo4/y6KOP8vDDD7NgwYJi9b8LFiwAoHv3w+7JKtXIkSM5//zzC5Pc8hhj6Nq1a+HrzcvLK5xCbcuWLcWS7NDQUPbs2cMPP/wAOAnvH3/8wc0331zYpuSCGcdSI1ywkMeRzJw5k+HDhx/1+Stb9f6XIiIiIjVWbl4u106/lucXPM9t/W/jnX+849EEuMDMn2YW1hWXJS0rjZk/z6ymiMqXllY81qLTnRU8SvPwww/Trl072rRpU6FHZmZmsWusWbOGm266ifPOO4+8vLzCxNjb2xt/f3+CgoLo06cPP/zwA0lJSZx//vmkp6czatQofH2rvp9Xr15Nr169GDlyJL///nuZ7ZYtW0ZOTtkzflQWjQSLiIgIGdkZXPL6JXy9/mseG/EY9w+53+PLEcPfyyRb/v66vujCHAW1whZbI5ZRfuWVV1i0aBGffvpp4baSpQbW2lJHrENDQznppJNKvemsqFdffZWbbrrpsFrjskbBC0obTj/9dJYsWcLAgQMZMWIEb7/9NlOnTmXBggW0bNmy1GN37NhRWKtcloSEhFK3u1wuMjIyWL9+PYMHD2bu3LmcccYZzJw5s9iKeCWPufDCCznllFNYtmxZudc9XkqCRURE6rnkjGSGvTiMlX+s5JUrXmF83/GeDqnQxr0bycz9e8QzyC+Ik5qdxNMXP82Ezybw2/7fCqdS8+QyyhkZGfz000+sXLmSiRMnltu2ZOlBAV9fX/Lz84mPjy/3+NTUVKDskoWFCxcW+yAQHR0NOMn3fffdx6pVq1i3bh1paWlMmTKFPn36MG/evGI1wgUKZq44Fj/88ANpaWnMnDmTXr16MW/ePAYMGFC4v0GDBqxevZqNGzcWJvBz584lKSmpWsollASLiIjUY/uS9zHohUFs2reJj274iDFnjPF0SMXM/mU2+a78wtHfx0Y8Vjg1W78H+jF5/mQe/PJBsvOyyXfle2wZ5fnz55OTk8P06dMZO3YsQKkjqEuWLGH27NnA4bNG5OTk8Pvvv9O8efMKXTMvL++wOtzc3Fz69OnDF198AcC7777LY489xtq1a7nnnntYtmwZs2bNKlyy+csvv6R3797cd999zJ8/v1gsAL///vsRF9F45513uO666w4rYTjrrLMYO3Ysw4cPZ+TIkYcdd8899zBx4kROPvnkwm1eXl5ccMEFxeqVq4qSYBERkXrqj4Q/iJ0cy/7U/cy+bTbndzrf0yEd5pO4T8pdmOPugXczvMtwxrw2hvW71/NJ3CfcM/Ceao9z7NixhIWFFSbA4KzgVtL27dt59tln6dWrF7179y62Lykpifbt2xcumlGWadOmcccdd5CZmXlYfXFGRgY+Pj6F8wwHBgaSk5PDZ599xoYNG5g3b16x0d2ePXvy73//myuuuKLYeQrqjb29vY94w1vBKG5SUtJh+4rObVzSTTfdxE033VTuuauSlk0WERGph9buXMugFwaR58pjzm1zOKPNGZV27oosZVtRw6YM47wO55W7MAc4U6lNnj+ZJVuWVHgeY0/IzMwkIyODJk2aHLYvPT2dvLy8YgtlVBZrLQcPHiQ8PLzSz+1Jx7NsspJgERGRembZb8sY9tIwQgJCmH/nfDo071Cp56/MJFikPMeTBGuKNBERkXpk1rpZDJw8kKhGUaz616pKT4BFagslwSIiIvXE9JXTuWjqRZwafSrL71tOy8alT4slUh8oCRYREakHnv32Wa6dfi39OvRj4V0LCW9Yt2pDRY6WkmAREZE6zFrLv/73L+797F5Gnz6aWbfOIjgg2NNhiXicpkgTERGpo/Ly8xj/3nimrZjG+D7jeenyl/D2Kn2BBZH6RkmwiIhIHZSVm8Vlr1/GF2u/4KGhD/Hw8IdrxDLIIjWFkmAREZE6JjUzlREvj2DJliVMuXQK/+z/T0+HJFLj1LskWB+CReRoeWA6dZFjlpCawOAXBrN+z3rev/59Lu9xuadDEqmRdGOciIhIHbE9cTvnPH0Om+I38dUtXykBrkZJSUlcc801LFmypMqvtX37dlasWEFeXl6F2ltrueqqqxgzZswxXe+zzz7jkksuYe/evcd0fGnmzp1LTExMpZ7zaNW7kWAREZG6aMOeDcQ+H0tWbhYL71pIzxN7ejqkeiU/P58ZM2bQt2/fwm2JiYkkJiaWeUxYWBjNmjU76mvNmDGDhx9+mMzMTHx8/k7lUlJSyMjIwN/f/7Alpn18fHjvvfeIi4ujbdu2hdtdLhdZWVmEhoYSFBR02LXS0tK45557OP/884mKijrqWMvSuXNndu3axVtvvcUDDzxQuD0vL4/s7GwaNGhQadcqk7W22h+nn3669RTni0099NBDj4o/RGq6lVtX2tDbQm3UPVH2l92/eDocu3HjxjL3efrfc1X9+05KSrKAff/99wu3PfrooxYo83H77bcf07WmTJliAetyuYptf/LJJ8u9XnmPWbNmlXqtK664osxjGjRoYLdu3VpurI899tgxxZOUlFSh96K8/9YKAHHWHp6PaiRYRESkFpvzyxxGvTqK6NBo5t05j5jwGE+HVC95eztTzxUdgfXz86NZs2bEx8cf1v6UU07Bz88PgOnTp/Phhx/i6+tbrE1YWBjvvvvuYccWtCs528dtt93G+PHj8fX1JTU1lWeeeYZRo0bRvXv3wjbWWi6++GIGDhzIuHHjcLlc5OTklDoK/Mwzz/D555/z1Vdf0a5du8Ltv//+O8OHD2fSpEnFRpVLU/AebNiwodx2BbHl5uaSmZlJSEjIEdsfLyXBIiIitdT7373PNdOvoXOLzsy9fS4RIRGeDqneeeKJJ8jIyCA/Px9w6mc3btyIy+WiSZMm5R5bkASfcMIJxMbG4ufnV5jYfv7556SlpbFlyxZycnKKJcj79+8HYOPGjeTk5NC6dWvCwsIICgoqTGazsrJ47733+PXXX5k3b17hsb/++iuzZ8+mf//+BAQEAJSaAD///PNMnDiRDz74gKFDhxZLuCdOnEjfvn0ZP378Ed8fLy8vvL29CQ93Vii01hITE8Ojjz7K2LFjC9udcMIJXHvttTz44INHPGdlURIsIiJSC01ZOIXbP7qdvif15ctbviQksOpHzuRw8fHxpKWl8ccffwBw8OBBdu3aBUBkZCT5+fls3779sONyc3ML63nPPfdczj333GL7Z8+eTbt27bjxxhtZvXo1wcHBhYloVlYWAL169SIzM5P33nuPgQMH8ueffxIQEFCYXF922WVs3ryZLVu24O/vDzhJeoMGDRg8eDDbt28vHAnOycmhZcuWhIWFMXPmTCZOnMjVV1/NpZdeymWXXVY4wp2fn4+XlxfGmMLE3OVyceGFF/L555+X+h55eXkRHx9PUlIS/v7+JCQkkJCQUOx9yc7OJiUlhT/++IPMzEzatWtXGHOVKa1GoqofqgnWQw89atNDpCZxuVz2wS8etFyPvejli2xmTqanQzpMfawJvu222yxgP/zww8JtL774ooWy617/85//WGut3b9/v73ooovs/v37C4+NiIiwH3zwgc3KyjrsWq+88oqlRPCLFy8u91oVeRSNfdu2bTYvL89mZ2cXu06LFi3spEmTim0bMmSIveKKK0p9X5566ikbExNjH3nkERsUFGRDQ0MtYIODg22TJk0KH15eXoX7/f397e+//16h9/14aoI1RZqIiEgtke/K5+b3b+axrx/jul7X8cmNnxDgG+DpsASYP38+AAkJCfz444+F25s1a3ZY8mWt5eSTTy52/JYtWxg8eDBpaWnExcWRkJBA79698ff3L1bOUJazzz6bAwcOkJGRQXZ2NpmZmRV6/PXXX6SlpZGQkMCIESMAZzS7YcOGpKWlkZGRQXJycuHDWktWVlaxbXl5ebhcLpKSkti9eze5ubmFceXk5ODv789DDz3EX3/9RVJSEgEBAbz44ouFs2ckJibSsmVLHnjgAZKSksjKyuLEE0+sjG4pl8ohREREaoHs3GyumnYVn675lH8N/hdPXPSElkGuIdasWcOmTZsAeOmll3j00UdZvXp1hY+PiIhg4cKF9OrVi5EjR9K1a1c6d+5MdHQ069atY+DAgXzzzTdccMEFZZ7Dz8+vsO62V69erFy5skLXDg0NJSkpieDg4MJtY8eO5ZtvvinzmAcffLDU2t0PP/wQgE2bNtGhQwfAKd0oOd1Zbm4uU6ZM4YsvvijclpCQUCx5rg5KgkVERGq49Kx0Lpp6EQs2LeDZ0c9yd+zdng5JinjxxRc5+eST+fXXX5k4cSLvvPMOI0eO5KqrriI/P5/NmzcfdkxOTk6x3yMjI5k9ezZnn302Cxcu5LHHHgPgtNNOY+jQoUycOJHBgwdX6IOPv78/gwYN4u233y633dNPP81HH3102PZPP/0UYwz+/v6HXS86Opo77riDe+65p3Db0KFDCQ8PZ/r06WRlZRXWJAOkpqYSGhqKtZbU1FT8/f2ZNWvWYecdP358tYz+FqUkWEREpAZLTEvkgikX8NPOn5h+7XTGnj3W0yFJEb/99hvvv/8+r776Ktdffz2+vr68++673H///VhrSUxMpGPHjhU6V/v27bnlllt49NFHi42ePvjgg/To0YOZM2cycuTII56n4Ma1ogtplNeupMDAQAD27NmDn59fsZkpipZDFMjLy8MpvaVwxokC+/fvJzIykpSUFMLCwo4Y+4cffsill156xHaVQTXBIiIiNdTOgzvp/UxvftnzCzNvnqkEuIbJz89n/PjxtGvXjlGjRhVuj46OZsaMGTRo0KDCNcEAhw4d4qWXXqJz5878+9//ZsuWLQCceeaZ9O7dmwMHDlQorszMTObMmUPTpk3LfTz33HNkZ2eXeZ6TTjqJiIgIwsLCCh979+7lwQcfLLbt22+/LbOU4c8//+SEE04gJCSEPXv2kJCQwIknnshdd91FWloaaWlpxMfH0759e0aNGlVtCTAoCRYREamRNu3bxDlPn8PelL18e8e3DDttmKdDkhKMMbRo0YJp06YdcdS1Im644QbCw8P57rvv6NKlC1deeWXh/MOLFy/mxhtvrNB55s+fX5hg/uMf/yAwMJCUlBTS0tLo2LEj9913X+H+nTt3lnme9PT0w5L3Fi1aMGnSpGLbHnnkEU455ZTDjk9JSWHdunV07doVLy8voqKiaNq0KdOnT+fFF1/k66+/JiAggFtuuQVfX1/eeuutY3vjjpHKIURERGqYH7b9wAVTLsDHy4dl9y7jtJaneTokKYWXlxfvvPMOxhjS09OP+viCEgKAhx9+mNmzZ7Nq1SqCgoJ47bXX6NatG8888wwTJ04sXJGuIgrKGXJzc1myZAlnnXVW4QpsXl5e+Pr6FrsRLj09HS8vr1IXzaiIhx56qNTt8+bNIz8/nz59+hTb3qtXL6ZOncpVV13FpEmTSEtLY9GiRdWySlxRGgkWERGpQeZvnE+///ajUWAjVk5YqQS4hiuoqS1IaIsmtvn5+ezfvx9jzGGPX3/9ldzcXFwuFxMmTOCxxx7jvffeo2vXrgB07tyZ+++/n27duh12zYrOonD//ffz559/FruJrbTj586dS+fOnVm/fn2553O5XGRmZlbo2gDPPfcc/fr1K7ZyXlpaGrNmzWLJkiUYY1i3bh3Z2dmFs0Vs3bq13BKNyqSRYBERkRrikx8/4cppV9KxeUfm3j6X5qHNPR1SpSuSI9YpBYllQfkCODeMhYeHs3z58sPaDx8+nNzcXPbt28e8efOYMWNGsbpicEaHi/ryyy/58ssvmTdvHk2bNj3snHl5eWzZsoXFixczY8YM1q5dy6RJk4pNrebt7c1XX33FFVdcQUhICPv37+e5557jwIEDREdHl/n6xo4dy9KlSzl06BAtW7Y84vuRmJhISkoKd999N7/++it3330327Zt448//qB58+YMHz6c5cuXc9JJJ/HRRx/x1Vdf8dprr5Gamgo4HwLi4uKKzTRR2ZQEi4iI1ACvLHmFWz64hXNOPIdZ/5xFaFCop0OSo1AwQlp0FDMrKwtvb+/COXOL8vPzIycnhxYtWhAXF1ehcoeoqCiWL19O//79ueGGGw7bf8cdd/Dyyy/TsGFDxowZw8cff8wJJ5xQrM2FF17IE088wWmn/f0NQ7NmzZg+fTqNGzcu89rDhg0jPz+ff//734wePfqIsYaHh7NhwwbAKcEYPnw4UVFRnH766Ycl0ePHj2f8+PG4XC62bt3Kr7/+SmRkZJUmwADGeuAjWffu3W1cXFy1XxdA84qLyNGqqyNXUjNYa3n8m8d56MuHGHrqUD4e9zFB/sdWm1lTbNq0qcLTgtUVeXl5bN++naZNm9KoUSMAkpKSSElJISYmplpiSEhIYOPGjZxzzjnFpjWryyry35oxZo21tnvJ7RoJFhER8RCXy8UdH9/Bi4te5OqeV/Pm1W/i61M/kpe6xsfHh7Zt2xbbVjCFWHWJiIggIiKi2q5X2ykJFhER8YDcvFyuefsaPvjhA+4acBeTLp6El5fuVxepLkqCRUREqtlf2X8x+tXRzNkwhydHPsmEQRMqtByuiFQeJcEiIiLV6NBfhxj64lC+//N7Xr/qdW449/AbnOoCa60Se6lSx3tfm5JgERGRarInaQ8DJw9ka8JWPh3/KSO7jfR0SFXCz8+PzMzMY158QaQiMjMz8ff3P+bjlQSLiIhUg637tzLg+QEcTD/InNvm0K9jP0+HVGXCw8PZvXs34eHhNGzYEB8fH40KS6Ww1pKXl0daWhqJiYk0a9bsmM+lJFhERKSK/bTjJwa9MAiAJfcu4fTWp3s4oqrVqFEj/P39OXDgAAcPHiQvL8/TIUkd4uPjQ0BAAK1atSIgIODYz1OJMYmIiEgJizcvZsTLIwgLCmP+nfNpH9ne0yFVi4CAgAqtLCbiKZqLRUREpIrM/Gkmg14YRMuwlqz616p6kwCL1AZKgkVERKrAtOXTuPjVi+nWqhvLJyynRVgLT4ckIkUoCRYREalE1lqenvM0179zPbEnx7LgrgU0btDY02GJSAmqCRYREakk1lru/exe/jvvv1x25mVMv3Y6fj5+ng5LREqhJFhERKQS5OXncf2M65mxega3nncrL1z6gpZBFqnBlASLiIgcp8ycTC55/RJmrZvFI8Mf4cGhD2peXJEarkJJsDFmGtARmG2tfbyU/WHA+0BD4Fdr7fhKjVJERKSGSs5IZvhLw1nx+wqmXjGVm/re5OmQRKQCjvg9jTFmJOBtrT0biDLGtCul2VXAe9ba3kBDY0z3So5TRESkxolPiafvpL589+d3fHjDh0qARWqRiowE9wU+cT9fBPQCtpZocxA4yRgTCrQEdlZSfCIiIjXSnwf+JPb5WOJT4/n6n18Te3Ksp0MSkaNQkSS4AbDH/TwVaFtKmxXAEOA2YDOQVLKBMWYcMA4gOjqa7du3AxAWFoafnx/79+8HIDAwkIiICHbs2FFwHK1bt2bfvn1kZ2cDEBUVRXp6OqmpqQA0btwYHx8fEhISAAgKCiI8PJydO51c3Nvbm5YtW7J3715iY3OcgFe0oFWrVFq1SgNgw4YmuFxenHrqAQD27g1m69ZQ+vTZDUBGhg8rVkTTq9dugoKc5R+XLo2mXbtkoqLSAVi/vileXi5OOeUgADt3NmTnzhB69XLevrQ0P1avjqJPn134++cDsGhRKzp1SiQyMgOAn3+OIDAwjw4dDgGwbVsI8fHB9Oy5F4CUFH++/745/frtwMfHAjB/fmu6dEmgadNMAOLimtGoUQ7t2jnd8McfoSQmBtCjRzwAhw4FEBcXyYAB2zEGrIX582Po3j2exo2zAPj++0jCw7M48cRkALZuDSMlxY/u3Z1+OnAgkLVrIxgwwOmnvDzDokWt6dFjH40aOf20enUUkZHptGnj9NPmzY3JzPSha1enn+Ljg9i4MZx+/Zx+ys72ZunSlvTsuZeGDdVP6qea008pKTkkJTn9FBoaSkBAAPHxTj8FBAQQGRlZ+DcNICYmhvj4eLKynH6KjIwkKyuL5GSnn6r7715OjtNPLVq0IDU1lbQ0p5+aNGmCl5cXBw44/RQcHExoaCi7dzv95OPjQ3R0NLt37y5c9jY6Oprk5GTS051+atq0KS6Xi4MHnX5q2LAhISEh7Nnj9JOfnx9RUVHs2rWL/Hynn1q1akViYiIZGU4/RUREkJeXx6FDTj+FhIQQHBzM3r1OP/n7+9O8eXN27NiBtU4/tW7dmoSEBDIznX5q1qwZOTnV10+b9m9i7Edjybf5fHz1x7Rv0J7t27ern2pYP4H+Pamfyp6f2xS8AWU2MOYF4ENr7Xfu0ogO1tonSrR5H7jJWptqjLkLSLfWvl7WObt3727j4uLKvW5V0X0KInK0jvBnUuqZFVtXMPTFoTQMaMi3d3xLp6hOng5JRMphjFljrT2sVLcic7eswSmBADgN2F5KmyCgszHGG+gB6H8ZIiJS53y97msGPD+AyEaRrJywUgmwSC1WkST4C+AqY8xzwBjgV2NMyRkingReB1KAxsCHlRmkiIiIp72z6h0unHohp0SdwvL7ltOqSStPhyQix+GINcHuEoe+wADgGWttPLCuRJsfgJOrIkARERFPe27ec9z96d3079ifmTfPpGFAQ0+HJCLHqULzBFtrk/h7hggREZF6wVrL/TPv58k5T3Lx6Rfz3nXv4e/r7+mwRKQSaMU4ERGRUuS78rnpvZt4Y/kb3Hjujbx8xct4e3l7OiwRqSRKgkVERErIys3iijev4POfPueBIQ/w6IhHtQyySB2jJFhERKSI1MxULnz5QhZvWczkSyZz+/m3ezokEakCSoJFRETcElITuGDKBazbvY53r3uXK8+60tMhiUgVURIsIiIC7Di4g9jnY9mVtIsvb/mSCzpf4OmQRKQKKQkWEZF679c9vxI7OZaMnAzm3zmfc9qe4+mQRKSKVWSxDBERkTpr9R+r6f1Mb6y1LLt3mRJgkXpCSbCIiNRbczfM5fznzqdJcBNWTlhJ5+jOng5JRKqJkmAREamXPvz+Q4a9NIz2zdqzYsIK2jRt4+mQRKQaKQkWEZF656VFL3HFtCs458RzWHLPEpqFNPN0SCJSzZQEi4hIvWGt5eGvHuafH/6T4acNZ+4dc2kU1MjTYYmIB2h2CBERqRfyXfnc9uFtTF0ylWvPuZbXr3odH2/9b1CkvtK/fhERqfNy8nK4+q2r+fjHj7l34L08PeppLYMsUs8pCRYRkTotPSudUa+MYt7GeTxz8TPcO/BeT4ckIjWAkmAREamzDqYfZMiUIfy4/UfeuuYtrj3nWk+HJCI1hJJgERGpk3Yd2sXAyQP588CffH7z54zoMsLTIYlIDaIkWERE6pzN+zYTOzmWlMwUvr3jW/qc1MfTIYlIDaMkWERE6pS47XEMfmEwXsaLJfcsoWurrp4OSURqIM0TLCIidcaCjQs479nzCPYPZuW/VioBFpEyKQkWEZE64bM1nzHkxSHEhMew8l8raRvR1tMhiUgNpiRYRERqvdeWvsaY18ZwRswZLLt3GVGhUZ4OSURqOCXBIiJSa1lr+b9v/o/x741n8CmDmXfHPMIahHk6LBGpBXRjnIiI1Eoul4u7PrmLFxa+wJVnXclbY9/C18fX02GJSC2hJFhERGqd3Lxc/jHjH7z33Xvccf4d/Hf0f/Hy0pebIlJxSoJFRKRWycjOYMxrY/jml2/4vwv/j4kXTMQY4+mwRKSWURIsIiK1RtJfSQx9cSir/1zNa1e9xrhzx3k6JBGppZQEi4hIrbA3eS8DJw/kt/2/8cmNn3Dx6Rd7OiQRqcWUBIuISI33e8LvDHhuAInpicy+bTb9O/b3dEgiUsspCRYRkRrt550/M2jyIFzWxeJ7FtM9prunQxKROkC30oqISI21dMtS+j7bF39ff5bft1wJsIhUGiXBIiJSI3259ksGTh5Ii9AWrJqwig7NO3g6JBGpQ5QEi4hIjfP2yrcZOXUkXVp2Yfl9y4luHO3pkESkjlESLCIiNcqkbyfxj+n/4PyO57PgrgU0CW7i6ZBEpA7SjXEiIlIjWGu577P7eHbes1xyxiW884938PPx83RYIlJHKQkWERGPy8vPY9y743h75dvc3Pdmplw2BW8vb0+HJSJ1mJJgERHxqMycTC574zK+XPsl/xn2H/4z7D9aBllEqpySYBER8ZiUjBSGvzyc5VuX8+JlL3Jrv1s9HZKI1BNKgkVExCP2p+5n0ORBbNi7gfeve5/Lelzm6ZBEpB5REiwiItVu24FtxE6OZW/yXmbdOotBpwzydEgiUs8oCRYRkWr1y+5fGDh5IFm5WSy4awE9T+zp6ZBEpB7SPMEiIlJtVmxdwbmTzsXLeLH8vuVKgEXEY5QEi4hItfhm/TfETo4lomEEK/+1kpNbnOzpkESkHlMSLCIiVe69795jxMsj6NS8EysmrKB1k9aeDklE6jklwSIiUqUmL5jMVdOuok/7Piy6exFNGzb1dEgiIkqCRUSkalhreWDmA9z58Z2M7DaSb277hpDAEE+HJSICaHYIERGpAvmufG55/xZeW/YaN/S+gVeufEXLIItIjaIkWEREKlV2bjZXTruSz9Z8xsTBE/m/i/5PyyCLSI2jJFhERCpNWlYaF029iIWbFvLcmOe4c8Cdng5JRKRUSoJFRKRSHEg7wAUvXMDPu35mxrUzuPrsqz0dkohImZQEi4jIcdt5cCexk2PZcXAHX9z8BUNPG+rpkEREyqUkWEREjsvGvRuJfT6W9Ox05t85n17tenk6JBGRI1ISLCIix+z7P7/ngikX4Ofjx7L7lnFq9KmeDklEpEI0T7CIiByTeb/Oo/9z/QkNCmXlhJVKgEWkVlESLCIiR+3jHz9m6ItDadu0LSsnrOSEpid4OiQRkaNSoSTYGDPNGLPKGPPAEdpNNcYMq5zQRESkJpq6eCqXvXEZZ51wFkvuXUJko0hPhyQictSOmAQbY0YC3tbas4EoY0y7Mtr1BiKttbMqOUYREakBrLU88tUj3PLBLQw9dSjf3vEtoUGhng5LROSYVOTGuL7AJ+7ni4BewNaiDYwxvsAbwGxjzAhr7ZclT2KMGQeMA4iOjmb79u0AhIWF4efnx/79+wEIDAwkIiKCHTt2FBxH69at2bdvH9nZ2QBERUWRnp5OamoqAI0bN8bHx4eEhAQAgoKCCA8PZ+fOnQB4e3vTsmVL9u7dS2xsDgArVrSgVatUWrVKA2DDhia4XF6ceuoBAPbuDWbr1lD69NkNQEaGDytWRNOr126CgvIAWLo0mnbtkomKSgdg/fqmeHm5OOWUgwDs3NmQnTtD6NVrDwBpaX6sXh1Fnz678PfPd97QRa3o1CmRyMgMAH7+OYLAwDw6dDgEwLZtIcTHB9Oz514AUlL8+f775vTrtwMfHwvA/Pmt6dIlgaZNMwGIi2tGo0Y5tGuXBMAff4SSmBhAjx7xABw6FEBcXCQDBmzHGLAW5s+PoXv3eBo3zgLg++8jCQ/P4sQTkwHYujWMlBQ/und3+unAgUDWro1gwACnn/LyDIsWtaZHj300auT00+rVUURGptOmjdNPmzc3JjPTh65dnX6Kjw9i48Zw+vVz+ik725ulS1vSs+deGjZUP6mfak4/paTkkJTk9FNoaCgBAQHExzv9FBAQQGRkZOHfNICYmBji4+PJynL6KTIykqysLJKTnX6q7r97OTlOP7Vo0YLU1FTS0px+atKkCV5eXhw44PRTcHAwoaGh7N7t9JOPjw/R0dHs3r2bnNwcHpn3CO/EvcMl3S7h8YGPs3/vfpo2bYrL5eLgQaefGjZsSEhICHv2OP3k5+dHVFQUu3btIj/f6adWrVqRmJhIRobTTxEREeTl5XHokNNPISEhBAcHs3ev00/+/v40b96cHTt2YK3TT61btyYhIYHMTKefmjVrRk6O+ikvz/n3FB0dTXJyMunpzr8n9ZP6qT73U1lMwRtQZgNjpgFTrLXrjDGxQDdr7VMl2lwHDAFuBv4JxFtrXyzrnN27d7dxcXHlXreqaOVOETlaR/gzWefl5OUw9q2xfPTjR9wdezfPjHoGLy/dUiIitYMxZo21tnvJ7RX5K5YOBLqfB5dxTFfgdWttPPAecN6xBioiIjXHX9l/Mfyl4Xz040c8Peppnh39rBJgEakTKlIOsQanBOI74DRgSyltfgcKbg3uDuyolOhERMRjDv11iCFThvDDth948+o3ua73dZ4OSUSk0lQkCf4CWG6MiQIGA5caYx631hadKWIa8JYx5lLAF7i40iMVEZFqs/vQbgZOHsgfB/7gs/GfcVG3izwdkohIpTpiEmytTTXG9AUGAM+4Sx7WlWiTBoyuigBFRKR6/Rb/GwOeH0BSRhJz75hL35P6ejokEZFKV6Flk621Sfw9Q4SIiNRRa3asYdDkQRhjWHLPErq17ubpkEREqoTubhAREQAWbVpE30l9aeDfgBX3rVACLCJ1mpJgERHhf2v+x+Apg2ndpDUrJ6ykfWR7T4ckIlKllASLiNRzbyx7gzGvjaF76+4su28ZLcLKnlxeRKSuUBIsIlJPWWt5cvaTjHt3HANPHsi8O+fRuEFjT4clIlItKnRjnIiI1C0ul4t7Pr2H5xc8z+VnXs70a6fj6+Pr6bBERKqNkmARkXomNy+X62Zcx7vfvctt/W/j+THPaxU4Eal3lASLiNQjGdkZXPL6JXy9/mseG/EY9w+5H2OMp8MSEal2SoJFROqJ5Ixkhr04jJV/rGTqFVO5qe9Nng5JRMRjlASLiNQD+5L3MXDyQDbHb+ajGz5izBljPB2SiIhHKQkWEanj/kj4gwHPDyAhLYFvbvuGAZ0GeDokERGPUxIsIlKHrd25lkEvDCLPlceiuxdxZpszPR2SiEiNoNuBRUTqqGW/LaPPs33w9fZl+X3LlQCLiBShJFhEpA76au1XDJw8kKhGUaz61yo6Nu/o6ZBERGoUJcEiInXM9JXTGfnKSDq36Mzy+5bTsnFLT4ckIlLjKAkWEalDnv32Wa6dfi3nnXQeC+9eSHjDcE+HJCJSI+nGOBGROsBay7/+9y+e+fYZRp8+mnevexd/X39PhyUiUmMpCRYRqeXy8vMY/954pq2Yxvg+43np8pfw9vL2dFgiIjWakmARkVosKzeLy16/jC/WfsGDQx/kkeGPaBlkEZEKUBIsIlJLpWamMuLlESzZsoQXLn2B2/rf5umQRERqDSXBIiK1UEJqAoNeGMQve37h/evf5/Iel3s6JBGRWkVJsIhILbM9cTsDnh/AnuQ9fHXLVwzuPNjTIYmI1DpKgkVEapENezYQ+3wsmbmZLLhzAWe3PdvTIYmI1EqaJ1hEpJZY9fsqej/TG2MMy+9brgRYROQ4KAkWEakFZv8ym/OfP5/w4HBWTljJKS1O8XRIIiK1mpJgEZEa7v3v3mfEyyPoENmBlRNWEhMe4+mQRERqPSXBIiI12JSFU7hy2pX0atuLJfcsISIkwtMhiYjUCUqCRURqIGstD335ELd/dDsXdrmQObfPISQwxNNhiYjUGZodQkSkhsl35XPrB7fy6tJXua7Xdbx65av4eOvPtYhIZdJfVRGRGiQ7N5urpl3Fp2s+ZcKgCTw58kktgywiUgWUBIuI1BBpWWmMnDqSBZsW8OzoZ7k79m5PhyQiUmcpCRYRqQES0xK5YMoF/LTzJ6ZfO52xZ4/1dEgiInWakmAREQ/beXAnAycPZPvB7Xx+0+cM7zLc0yGJiNR5SoJFRDxo075NxD4fS2pWKt/e8S3ntj/X0yGJiNQLSoJFRDzkh20/cMGUC/Dx8mHpPUvp0qqLp0MSEak3NE+wiIgHzN84n37/7UdIQAgrJ6xUAiwiUs2UBIuIVLNPfvyEIVOGcGLTE1k5YSUnRpzo6ZBEROodJcEiItXolSWvcOkbl9KjTQ+W3ruU5qHNPR2SiEi9pCRYRKQaWGt57OvHuPn9mxnSeQjf3vEtoUGhng5LRKTe0o1xIiJVzOVyccfHd/Diohe5uufVvHn1m/j6+Ho6LBGRek1JsIhIFcrJy+Hat6/lgx8+4K4BdzHp4kl4eelLOBERT1MSLCJSRf7K/ouLX72YuRvm8uTIJ5kwaALGGE+HJSIiKAkWEakSh/46xNAXh/L9n9/z+lWvc8O5N3g6JBERKUJJsIhIJduTtIeBkweyNWErn47/lJHdRno6JBERKUFJsIhIJfot/jdiJ8dyMP0gc26bQ7+O/TwdkoiIlEJJsIhIJflpx08MemEQ1loW37OY7jHdPR2SiIiUQbcoi4hUgsWbF9P32b4E+gaycsJKJcAiIjWckmARkeM086eZDHphEC3DWrLqX6toH9ne0yGJiMgRKAkWETkO05ZP4+JXL6Zbq24sn7CcFmEtPB2SiIhUgJJgEZFjYK3l6TlPc/071zOg0wAW3LWAxg0aezosERGpIN0YJyJylFwuF/f97z7+O++/XHbmZUy/djp+Pn6eDktERI6CkmARkaOQl5/H9TOuZ8bqGdx63q28cOkLWgZZRKQWUhIsIlJBmTmZXPL6JcxaN4uHhz3MQ8Me0jLIIiK1lJJgEZEKSM5IZvhLw1nx+wpevvxlbj7vZk+HJCIix6FC3+EZY6YZY1YZYx44QrtmxpifKyc0EZGaIT4lnr6T+vLdn9/x4Q0fKgEWEakDjpgEG2NGAt7W2rOBKGNMu3KaPwsEVlZwIiIe1/BPznn6HLYmbOXrf37NJWdc4umIRESkElSkHKIv8In7+SKgF7C1ZCNjTD/gLyC+tJMYY8YB4wCio6PZvn07AGFhYfj5+bF//34AAgMDiYiIYMeOHQXH0bp1a/bt20d2djYAUVFRpKenk5qaCkDjxo3x8fEhISEBgKCgIMLDw9m5cycA3t7etGzZkr179xIbmwPAihUtaNUqlVat0gDYsKEJLpcXp556AIC9e4PZujWUPn12A5CR4cOKFdH06rWboKA8AJYujaZdu2SiotIBWL++KV5eLk455SAAO3c2ZOfOEHr12gNAWpofq1dH0afPLvz98503dFErOnVKJDIyA4Cff44gMDCPDh0OAbBtWwjx8cH07LkXgJQUf77/vjn9+u3Ax8cCMH9+a7p0SaBp00wA4uKa0ahRDu3aJQHwxx+hJCYG0KOH0zWHDgUQFxfJgAHbMQashfnzY+jePZ7GjbMA+P77SMLDszjxxGQAtm4NIyXFj+7dnX46cCCQtWsjGDDA6ae8PMOiRa3p0WMfjRo5/bR6dRSRkem0aeP00+bNjcnM9KFrV6ef4uOD2LgxnH79nH7KzvZm6dKW9Oy5l4YN1U/qJ8/3U5rvJr4Lu5akv3J47/L3aN+gPcnJyQQEBBAf7/RTQEAAkZGRhX/TAGJiYoiPjycry+mnyMhIsrKySE52+qm6/+7l5Dj91KJFC1JTU0lLc/qpSZMmeHl5ceCA00/BwcGEhoaye7fTTz4+PkRHR7N7927y8px+io6OJjk5mfR0p5+aNm2Ky+Xi4EGnnxo2bEhISAh79jj95OfnR1RUFLt27SI/3+mnVq1akZiYSEaG008RERHk5eVx6JDTTyEhIQQHB7N3r9NP/v7+NG/enB07dmCt00+tW7cmISGBzEzn31OzZs3IyckhKcn59xQaGqp+Uj+pn9RPtGhR9tztpuANKLOBMdOAKdbadcaYWKCbtfapEm38gHnAhcAX1tq+5Z2ze/fuNi4urtzrVhXdwyIiFdJsOcQOg9yG/Prfb+kU1cnTEYmIyDEwxqyx1h62ln1FaoLT+bvEIbiMY/4FvGytTT7mCEVEaoqWX8PgWMiMhFkrlQCLiNRBFUmC1+CUQACcBmwvpc35wC3GmCVAF2PMm5USnYhIdWv7Dgy4EJJOga+Xw1+tPB2RiIhUgYrUBH8BLDfGRAGDgUuNMY9bawtnirDWnlvw3BizxFp7faVHKiJS1U55Ds66G/b0hwUzIbehpyMSEZEqcsQk2FqbaozpCwwAnrHWxgPrymnft7KCExGpHha6/xu6PAXbRsHi98Hl7+mgRESkClVosQxrbRJ/zxAhIlJ3mHw4Zzx0eBM2jYNVU8F6ezoqERGpYloxTkTqL+8s6HsFtPkcfr4f1jwGaAoZEZH6QEmwiNRPvqnODXBRi2H1ZPj1dk9HJCIi1UhJsIjUPwEJMGgwNF4HS96F36/0dEQiIlLNlASLSP0SvAMGxULwLpj/Jewa4umIRETEA5QEi0j9EfqrswiGTwbMmQ/7z/F0RCIi4iFKgkWkfohYDbFDID8Avl4GSZ09HZGIiHhQRVaMExGp3aLnwuDzIbsxzFqpBFhERJQEi0gdd8KHEDsMUtrD1yshvY2nIxIRkRpASbCI1F2dXoLzrnBqf79ZApnNPB2RiIjUEEqCRaQOstDtP3D2P2HHcJg7F3IbeTooERGpQXRjnIjULSYfet4GnabClmthxetg9adORESK0/8ZRKTu8MqBPlfDiR/D+nvhh6fRMsgiIlIaJcEiUjf4pMP5IyF6Pnz/DPxyr6cjEhGRGkxJsIjUfv4HYeAFEB4HS9+Crdd6OiIREanhlASLSO3WYBcMGggN/4QFn8POEZ6OSEREagElwSJSezXa7CyD7JcMc7+F+D6ejkhERGoJJcEiUjuF/wiDBoP1hm+WwsGuno5IRERqEc0TLCK1T9QCuKAf5DaEWSuUAIuIyFFTEiwitUvMZzBwCKTHwKyVkNrO0xGJiEgtpCRYRGqPDq9B/zGQ2B2+XgYZUZ6OSEREaiklwSJSC1jo8n/QazzsGgyz50NOmKeDEhGRWkw3xolIDeeCs+6CU16ArVfCsrfA+no6KBERqeWUBItIzWVy4dx/QLv3YMPt8N1z6AssERGpDEqCRaRm8s6A/qOh1WyIexzW/hswno5KRETqCCXBIlLz+CXBwKEQsRpWvAqbb/R0RCIiUscoCRaRmiVor7MMcqPfYOEnsP1iT0ckIiJ1kJJgEak5QrY6yyD7J8K3s2Fvf09HJCIidZSSYBGpGZr8DIMGAS6YvQgSz/B0RCIiUofpNmsR8bzIpTCkL+T7w9fLlQCLiEiVUxIsIp7V+gunBvivFs4yyCkdPB2RiIjUA0qCRcRz2r0N/UfBodOcEeC/Wno6IhERqSeUBIuIZ3SeBH3+AXvPh9kLIbuJpyMSEZF6RDfGiUg1s3DmfXDqs/DHJbD0HXD5eTooERGpZ5QEi0j1MXnQ+wZoPx023gSrXwTr7emoRESkHlISLCLVwzsT+l0Krb+Cn/7jPLQMsoiIeIiSYBGper4pEDscIpfDqhdh462ejkhEROo5JcEiUrUC98PAQdB4Ayx+H/68zNMRiYiIKAkWkSoUvA0GD4CgfTBvFuwe5OmIREREACXBIlJVwn5xFsHwzoI5CyChp6cjEhERKaR5gkWk8jVbAUPPBYyzCIYSYBERqWGUBItI5Wr5jVMCkdXUWQY5+WRPRyQiInIYJcEiUnnavgsDRkByJ5i1AtJjPB2RiIhIqZQEi0jlOHky9L0a9vWBbxZDVoSnIxIRESmTkmAROU4Wut8PPe+EbSNh3jeQG+LpoERERMql2SFE5NiZfDj7Zuj4Omy+Hla+qmWQRUSkVlASLCLHxisb+l4JJ3wGaydC3P+hZZBFRKS2UBIsIkfPNw3OvxBaLILv/gsb7vJ0RCIiIkdFSbCIHJ2AAzBwMDRZC0tmwO9XezoiERGRo6YkWEQqrsFOZw7g4J2wYCbsHObpiERERI6JkmARqZjQjTA4FnzSYc482N/b0xGJiIgcMyXBInJkTb+DgUPA5QffLIVDp3k6IhERkeOieYJFpHwtvoUL+kNOqLMMshJgERGpA5QEi0jZTvgYYodBajsnAU47wdMRiYiIVIoKJcHGmGnGmFXGmAfK2N/IGDPHGDPfGDPTGONXuWGKSLXrOBXOuwwSzoJvlkBmpKcjEhERqTRHTIKNMSMBb2vt2UCUMaZdKc2uAJ6z1g4A4oFBlRumiFQfC10fgXNugZ1DYe63TimEiIhIHVKRG+P6Ap+4ny8CegFbizaw1k4t8mtTIKHkSYwx44BxANHR0Wzfvh2AsLAw/Pz82L9/PwCBgYFERESwY8eOguNo3bo1+/btIzs7G4CoqCjS09NJTU0FoHHjxvj4+JCQ4Fw2KCiI8PBwdu7cCYC3tzctW7Zk7969xMbmALBiRQtatUqlVas0ADZsaILL5cWppx4AYO/eYLZuDaVPn90AZGT4sGJFNL167SYoKA+ApUujadcumaiodADWr2+Kl5eLU045CMDOnQ3ZuTOEXr32AJCW5sfq1VH06bMLf/985w1d1IpOnRKJjMwA4OefIwgMzKNDh0MAbNsWQnx8MD177gUgJcWf779vTr9+O/DxsQDMn9+aLl0SaNo0E4C4uGY0apRDu3ZJAPzxRyiJiQH06BEPwKFDAcTFRTJgwHaMAWth/vwYunePp3HjLAC+/z6S8PAsTjwxGYCtW8NISfGje3ennw4cCGTt2ggGDHD6KS/PsGhRa3r02EejRk4/rV4dRWRkOm3aOP20eXNjMjN96NrV6af4+CA2bgynXz+nn7KzvVm6tCU9e+6lYUP1kyf6yeJiNU+T3up1otJH0ck8RcLJaWzc6F+v+yklJYekJKefQkNDCQgIID7e6aeAgAAiIyML/6YBxMTEEB8fT1aW00+RkZFkZWWRnOz0U3X/3cvJcfqpRYsWpKamkpbm9FOTJk3w8vLiwAGnn4KDgwkNDWX3bqeffHx8iI6OZvfu3eTlOf0UHR1NcnIy6elOPzVt2hSXy8XBg04/NWzYkJCQEPbscfrJz8+PqKgodu3aRX6+00+tWrUiMTGRjAynnyIiIsjLy+PQIaefQkJCCA4OZu9ep5/8/f1p3rw5O3bswFqnn1q3bk1CQgKZmU4/NWvWjJwc9ZP6Sf2kfjq8n8piCt6AMhsYMw2YYq1dZ4yJBbpZa58qo21P4HFrbf/yztm9e3cbFxdX7nWritGqriKl88qBPmPhxI9g/d3wwzPotgHHEf5MiohIDWaMWWOt7V5ye0VGgtOBQPfzYMr4v6IxpjHwIjDqWIMUEQ/x+Qv6j4KW38IPT8H6+wB9YhQRkbqrIsM8a3BKIABOA7aXbOC+Ee4TYKK1dkelRSciVc//oDMFWov5sOxNWD8BJcAiIlLXVSQJ/gK4yhjzHDAG+NUY83iJNtcBpwP3G2OWGGMuqdwwRaRKBO2GoedC47Ww8DP47TpPRyQiIlItjlgOYa1NNcb0BQYAz1hr44F1Jdq8ArxSFQGKSBVptAUGxYJ/Enw7B/ad5+mIREREqk2Flk221ibx9wwRIlLbNVkDgwYBxpkD+GA3T0ckIiJSrXTrt0h903wRDOkLeQ1g1golwCIiUi8pCRapT2L+B4MGQ3prZxnk1PaejkhERMQjlASL1BcnvQH9xkDi6fDNMsgoewJxERGRuk5JsEidZ+G0J6H3ONgzEObMh+zGng5KRETEoyp0Y5yI1FYu6HEPdH4efr8clk4H6+vpoERERDxOSbBIXWVy4dzroN278Os/YfVk9OWPiIiIQ0mwSF3knQH9x0CrbyDuUVj7AFoFTkRE5G9KgkXqGr9kiB0GzVbCyqmw6SZPRyQiIlLjKAkWqUsC98HggdBoMyz6CLaN8XREIiIiNZKSYJG6IuR3ZxnkwASY9w3sGeDpiERERGosJcEidUHjtc4yyF55MHsRHDjT0xGJiIjUaLpVXKS2i1wGQ/uAyxe+Xq4EWEREpAKUBIvUZq2+gkEDIaO5swxyckdPRyQiIlIrKAkWqa3aTYfzR8KhzjBrBfzVytMRiYiI1BpKgkVqo87PQp9rYd95MGchZId7OiIREZFaRTfGidQqFs74F5z2DPw5Gpa8Cy5/TwclIiJS6ygJFqktTB70uhFOegs2jYdVL4H19nRUIiIitZKSYJHawDsLzrsMYr6Anx6Enx5ByyCLiIgcOyXBIjWdbyoMGAFRS2D1C/DrbZ6OSEREpNZTEixSkwXuh4GDofEvsPg9+OMKT0ckIiJSJygJFqmpgrfD4AHQYA/M+wp2D/Z0RCIiInWGkmCRmihsAwyKBZ9MmL0AEs72dEQiIiJ1iuYJFqlpIlbB0N7O86+XKQEWERGpAkqCRWqS6NlwwfmQFQ6zVkFSZ09HJCIiUicpCRapKU58H2JHQHIHmLUS0mM8HZGIiEidpSRYpCY4eQqcdyXsPwe+WQJZEZ6OSEREpE5TEiziURZOfxB63g7bL4S5cyE3xNNBiYiI1HmaHULEU0w+nH0LdHwNtlwHK14Fq3+SIiIi1UH/xxXxBK9s6HsVnPAprJsAPz6JlkEWERGpPkqCRaqbbxqcPxJaLIDvJ8Ev93g6IhERkXpHSbBIdfJPhIEXQPhPsPRt2HqNpyMSOWpGX1qIyFGy1tMRHE5JsEh1abATBsdC8A5Y8DnsHO7piEREROotJcEi1SF0k7MMsl8qzP0W4s/1dEQiIiL1mpJgkarW9AenBMLlA18vhUNdPB2RiIhIvad5gkWqUov5cEE/yAlxVoFTAiwiIlIjKAkWqSptPoHYIZB2gpMAp53o6YhERETETUmwSFXo+Ar0uxQOnOmUQGQ293REIiIiUoSSYJFKZaHro3DOzbDrApgzD3LCPB2UiIiIlKAb40QqjQt63gEnvwhbr4Jl08D6ejooERERKYWSYJHK4JUD514LbT+AX+6E759FX7SIiIjUXEqCRY6Xz1/Q/2JoORd+fALW/QvQkloiIiI1mZJgkePhfwhih0LT72H567DlBk9HJCIiIhWgJFjkWAXtgUEDodFWWPQJbB/l6YhERESkgpQEixyLkN9gcCz4H4S5c2BfP09HJCIiIkdBSbDI0WqyBgYNBizMXgyJ3T0dkYiIiBwl3b4ucjSaL4Yh50FeIHy9QgmwiIhILaUkWATAJx36jXF+lqX1TBg0CP5q6SyDnHJS9cUnIiIilUpJsAhA1EI44VOIWlT6/pPedKZBS+wGXy+DjOjqjU9EREQqlZJgEYCYmWBxRnuLsXDq09D7BtgzAOYsgOwmnohQREREKpGSYBEstPraWd+i9SzndwBccOa9cOa/4I9LYf5XkNfAg3GKiIhIZVESLBK6EbyznOfemRC6CUwunPsPOPW/8OstsPh9cPl5Nk4RERGpNJoiTaTlbDB5znPjglZfQrPVzqjwmofh54fQMsgiIiJ1i5JgkRM+AZ9s57lPFnR5Anz/gpUvw6abPRubiIiIVIkKJcHGmGlAR2C2tfbxY20j4hH9R0Gbz8ven1+izME33Rn4PecW51HStpGw8H+VGqKIiIhUryPWBBtjRgLe1tqzgShjTLtjaSPiMT8+BYldILeMm9q8c4r/XlblQ24DSOzqnE9ERERqtYrcGNcX+MT9fBHQ6xjbiHhGajv4Mg7WPOKs9OY6yvtBXV7OcWsehS/inPOJiIhIrVaRcogGwB7381Sg7bG0McaMA8a5f003xmw5ulBFjoMFNgCb8CeEE/HCH1OBD4EWFy5XFqmZf5J/dzbcXeWhSs1jdF+kSEWFA4meDkJqHg//HW1d2saKJMHpQKD7eTCljx4fsY219nXg9QpcT8QjjDFx1truno5DRKS20t9RqU0q8r3wGv4ubzgN2H6MbUREREREaoSKjAR/ASw3xkQBg4FLjTGPW2sfKKfNWZUdqIiIiIhIZTHW2iM3MiYMGAAss9bGH2sbkZrMGDPOXbYjIiLHQH9HpTapUBIsIiIiIlKXHOVcUSI1nzHGzxjje4Q2XsaYAGOMX5FtHd2zmGCMCTfGfGeMae7+/XdjzCj385uNMeuq8jWIiNQ1xhhvY0yIp+MQKaAkWOqifwM5xhhb1gPIBzKBousiewETjDFPAl8CvwKH3Pt83McAZABJUJhw69+RiNQpxpgOxpg2Jbb9xxgzs+jgwVGczwDrgQmVFaPI8VI5hNQ5xpjGOHNX5+HMEAzwgvvn7e6fXoA/kGStTS5ybBfgJ2AecD8QV4FLdrXWrj3euEVEagpjzMvAWOB2a+0094f934A3rbXlLptpjAktY9erODNI9SxtZ9G/xSLVQUmw1AvGmOkA1tprymnTBJgFnAx8C1yKsxx4rjFmO3CPtfYzY8wNwJXW2j7GGH8g11rrquKXICJSbdwjt/8CRuFMgToM+AD4q4xDfIEUa22UMSYbOOrRYiDIWpt5LPGKHAt9jSt1ijHG3xhTkan/Ctp7u2uDWwI/4/zhHgWcb611WWtz3U0P4owsg7Ma0iYAa222EmARqWus40mcKU+9gGdwvknrB0Raa0OLPoCrgBT34dnALUBYBR/DihwnUm0qnCyI1BJPA7ebMtZnNMaMLWXzUuA8YBVwG06tcJgxpjWwHwgA+ruPDwUWA4vdz7OstVmV+xJERDzHGBOA803Yh9babGPMmzgJ7sc4i2GNBua6R4sD3KO33jj3YhicFWQzgByceylybImvnd3tfHEGHhKBHTglahoJlmqjcgipU9wjuqEUrwf2BlbjfOg7F2eZb4rsy7XW/lbkHM2BnThfAfYDnijnkpOstfdVVvwiIp5mjBmEswhWAs7Nw8uBcOBGYBzOyLALSAUOWWu7GGMuA+4BzgBOxfkbuginBvhIwlQPLJ6gkWCpU6y1u4BdRbcZY2JxRhsSgPOstZPKOt696MtsnNGLCCALWGqt7eveb3HfCGeMWYJGLUSkjrHWzjXGdALeAppba1PcfxtvAfoCVwDJ1tqHixzmDeS5y8PWQmEybXDKHFzAVHfbm93b/dyP1Cp+SSKlUhIs9cFE4CucUYlHjDEzrLUJJRu5l/3+BmfUIwFoyt+jyWXRVykiUudYa/80xvTDqVzwxSkNO9FaG2+MuaKgnTHGG6dkzJu/75soOEex1WONMTnu7clVHL5IhSgJljrNGHM90AfojjNH5c3Ah8aYWGttfpF2zXBujPsSuAMnGS644a2PewS4wM9Fao6XVGX8IiIe1Mpau90YMwaYDGS5/xY2BlzGmGtwRnR/Az6iSBLsnm2nCZDL34MFwe59Me7fvXBGglOstfuq+sWIlKTZIaTOcq/w9jLwnLX2J2ttHnAlzhyVb7hHMACw1u4HrrbWjnN/nRfK33c6r+Tvu5jBqSsOc28XEamrXjPG3GKt/RA4EehvrY3BKZOY7H4+1lo7gMNHgq/EGXhYh1MesRYY7n4U/P4zzrzs91b5KxEphZJgqXOMMUHGmGeBT4EPgcIb16y164ERwMXASmPMGUX2fes+vjHQBdjs3pVnrU0u8hVemvt5sa/+RETqCvfsNwWz5oDzbdqbpTRd7P5ZLAm21r5grQ2w1oYUmUbtA+AD9/OTgKeABtbau6rkRYgcgZJgqTOMMWHGmNtxktd/Av+01l5Tch5fa+184HScr+F+MMZ8Z4w5yRjT0BhzPvA58Lu1dhPOV319iiy3DE45hMUpsyh9LjYRkdrtYuA3a+3PRbb5GGMicMoamhtjzi66j6MbGGiJs8T9c8cdqcgxUk2w1CW5OAtdLAEestZuL6uhtXarMaY7zh/6k6y1W4wx4cAcnK/oRrmbBlJkdoii3LNDBFZi/CIiHueew/cWnAGBArlAG5yR3xT347Yi+wNwJ8HuOdYtzjzBRQUCfsaYDjhTVf6f+3Kn4azPsb7yX41I2TRPsNQpxhiv41nBzRjTzF0fXPB7IyCw5F3OIiJ1lTGmJ85gwgBr7bIjtB0EXAbE4iyucZcx5g8gCicJPlKSYXBKKeKttW2PN3aRo6EkWERERIoxxpwE7LHWph+hXWOcuuGFwAPW2qTqiE+kMigJFhEREZF6RzfGiYiIiEi9oyRYREREROodJcEiIiIiUu8oCRYRERGRekdJsIiIiIjUO0qCRURERKTe+X/zhpYvppa//wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_competitive(cate_df, '店铺类型竞争度分析', 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d63be31",
   "metadata": {},
   "source": [
    "### 型号竞争度分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "447f7517",
   "metadata": {},
   "outputs": [],
   "source": [
    "type_top10 = calculate_compatitive(df, '型号').sort_values('预估销售额', ascending=False)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "b052c6c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_competitive(type_top10, '型号top10竞争度分析', rotation=60)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6df8eae",
   "metadata": {},
   "source": [
    "### 物理形态竞争度分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "9c84f5d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "physics = calculate_compatitive(df50, '物理形态')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "e5f3dada",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_competitive(physics, '物理形态竞争度分析', 60)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f580c1f9",
   "metadata": {},
   "source": [
    "#### 固体、净含量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "42ee6ac0",
   "metadata": {},
   "outputs": [],
   "source": [
    "solid = df50.loc[df['物理形态'] == '固体'] # 找到固体"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "3b4b5e4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>预估销售额</th>\n",
       "      <th>销售额占比</th>\n",
       "      <th>宝贝数量</th>\n",
       "      <th>宝贝数比</th>\n",
       "      <th>单宝贝平均销售额</th>\n",
       "      <th>相对竞争度</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>净含量</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2122422.34</td>\n",
       "      <td>0.651437</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>10404.031078</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20g</th>\n",
       "      <td>243594.06</td>\n",
       "      <td>0.074767</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>1194.088529</td>\n",
       "      <td>0.885228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118.5g</th>\n",
       "      <td>209308.20</td>\n",
       "      <td>0.064243</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>1026.020588</td>\n",
       "      <td>0.901382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.2KG</th>\n",
       "      <td>140739.32</td>\n",
       "      <td>0.043197</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>689.898627</td>\n",
       "      <td>0.933689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6个装</th>\n",
       "      <td>139575.50</td>\n",
       "      <td>0.042840</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>684.193627</td>\n",
       "      <td>0.934238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.17KG</th>\n",
       "      <td>133950.00</td>\n",
       "      <td>0.041113</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>656.617647</td>\n",
       "      <td>0.936888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12粒</th>\n",
       "      <td>36313.20</td>\n",
       "      <td>0.011146</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>178.005882</td>\n",
       "      <td>0.982891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170g</th>\n",
       "      <td>27011.40</td>\n",
       "      <td>0.008291</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>132.408824</td>\n",
       "      <td>0.987273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>020</th>\n",
       "      <td>23078.08</td>\n",
       "      <td>0.007083</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>113.127843</td>\n",
       "      <td>0.989127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>610克</th>\n",
       "      <td>13132.80</td>\n",
       "      <td>0.004031</td>\n",
       "      <td>204</td>\n",
       "      <td>0.007752</td>\n",
       "      <td>64.376471</td>\n",
       "      <td>0.993812</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             预估销售额     销售额占比  宝贝数量      宝贝数比      单宝贝平均销售额     相对竞争度\n",
       "净含量                                                                 \n",
       "1       2122422.34  0.651437   204  0.007752  10404.031078  0.000000\n",
       "20g      243594.06  0.074767   204  0.007752   1194.088529  0.885228\n",
       "118.5g   209308.20  0.064243   204  0.007752   1026.020588  0.901382\n",
       "2.2KG    140739.32  0.043197   204  0.007752    689.898627  0.933689\n",
       "6个装      139575.50  0.042840   204  0.007752    684.193627  0.934238\n",
       "0.17KG   133950.00  0.041113   204  0.007752    656.617647  0.936888\n",
       "12粒       36313.20  0.011146   204  0.007752    178.005882  0.982891\n",
       "170g      27011.40  0.008291   204  0.007752    132.408824  0.987273\n",
       "020       23078.08  0.007083   204  0.007752    113.127843  0.989127\n",
       "610克      13132.80  0.004031   204  0.007752     64.376471  0.993812"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solid_top10 = calculate_compatitive(solid, '净含量').sort_values(['预估销售额'], ascending=False)[:10]\n",
    "solid_top10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "61ce4861",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_competitive(solid_top10, '固体形态净含量竞争度分析', 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d80c92e",
   "metadata": {},
   "source": [
    "### 竞争度分析结论\n",
    "1. 灭鼠杀虫剂市场中,需要重点关注的产品类别是:灭鼠和蟑灭鼠中: \n",
    "2. 灭鼠中:\n",
    "    - 最大的市场集中在0-50的价格段,这个价格段竞争也很激烈\n",
    "    - 200-250这个价格段市场份额占10%左右,竞争度很低,是值得挖掘的高价市场\n",
    "3. 灭鼠0-50价格段的产品市场中:\n",
    "    - 10-20价格段市场容量大,竞争度低,值得进一步开发,20-30也不错\n",
    "    - 店铺类型方面天猫明显优于淘宝\n",
    "    - 市场份额高的型号是粘鼠板,然而型号0005市场份额还行,竞争度较低,值得开发\n",
    "    - 产品的物理形态基本都是固体,也是被大众认可的形态\n",
    "    - 当物理形态为固体,净含量为1时,市场份额高竞争度低,值得开发\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "91fefe39",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'top100' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-173-d19fb0c4f467>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mtop100\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'top100' is not defined"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a35bb18",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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